Overview

Dataset statistics

Number of variables62
Number of observations56
Missing cells1351
Missing cells (%)38.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.2 KiB
Average record size in memory498.3 B

Variable types

Numeric12
Categorical42
Unsupported8

Alerts

airdate has constant value "2020-12-06" Constant
_embedded.show.externals.tvrage has constant value "25100.0" Constant
_embedded.show.network.officialSite has constant value "https://www.hbo.com/" Constant
_embedded.show.dvdCountry.name has constant value "Ukraine" Constant
_embedded.show.dvdCountry.code has constant value "UA" Constant
_embedded.show.dvdCountry.timezone has constant value "Europe/Zaporozhye" Constant
url has a high cardinality: 56 distinct values High cardinality
name has a high cardinality: 55 distinct values High cardinality
_links.self.href has a high cardinality: 56 distinct values High cardinality
id is highly correlated with rating.averageHigh correlation
season is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 5 other fieldsHigh correlation
rating.average is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.averageHigh correlation
_embedded.show.network.id is highly correlated with number and 4 other fieldsHigh correlation
season is highly correlated with number and 2 other fieldsHigh correlation
number is highly correlated with season and 2 other fieldsHigh correlation
runtime is highly correlated with season and 4 other fieldsHigh correlation
rating.average is highly correlated with number and 6 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 8 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.averageHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.rating.averageHigh correlation
season is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
number is highly correlated with _embedded.show.network.idHigh correlation
runtime is highly correlated with _embedded.show.runtime and 2 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.rating.average and 4 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 1 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.averageHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.averageHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.averageHigh correlation
_embedded.show.network.id is highly correlated with number and 1 other fieldsHigh correlation
id is highly correlated with url and 32 other fieldsHigh correlation
url is highly correlated with id and 46 other fieldsHigh correlation
name is highly correlated with id and 42 other fieldsHigh correlation
season is highly correlated with id and 26 other fieldsHigh correlation
number is highly correlated with id and 30 other fieldsHigh correlation
type is highly correlated with url and 18 other fieldsHigh correlation
airtime is highly correlated with url and 39 other fieldsHigh correlation
airstamp is highly correlated with id and 44 other fieldsHigh correlation
runtime is highly correlated with url and 38 other fieldsHigh correlation
summary is highly correlated with id and 34 other fieldsHigh correlation
rating.average is highly correlated with url and 23 other fieldsHigh correlation
image.medium is highly correlated with id and 35 other fieldsHigh correlation
image.original is highly correlated with id and 35 other fieldsHigh correlation
_links.self.href is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.type is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.language is highly correlated with url and 42 other fieldsHigh correlation
_embedded.show.status is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with url and 33 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with url and 36 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with url and 36 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.updated is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with url and 27 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with url and 35 other fieldsHigh correlation
number has 2 (3.6%) missing values Missing
runtime has 6 (10.7%) missing values Missing
summary has 46 (82.1%) missing values Missing
rating.average has 53 (94.6%) missing values Missing
image.medium has 36 (64.3%) missing values Missing
image.original has 36 (64.3%) missing values Missing
_embedded.show.runtime has 12 (21.4%) missing values Missing
_embedded.show.averageRuntime has 4 (7.1%) missing values Missing
_embedded.show.ended has 41 (73.2%) missing values Missing
_embedded.show.officialSite has 1 (1.8%) missing values Missing
_embedded.show.rating.average has 51 (91.1%) missing values Missing
_embedded.show.network has 56 (100.0%) missing values Missing
_embedded.show.webChannel.id has 2 (3.6%) missing values Missing
_embedded.show.webChannel.name has 2 (3.6%) missing values Missing
_embedded.show.webChannel.country.name has 23 (41.1%) missing values Missing
_embedded.show.webChannel.country.code has 23 (41.1%) missing values Missing
_embedded.show.webChannel.country.timezone has 23 (41.1%) missing values Missing
_embedded.show.webChannel.officialSite has 29 (51.8%) missing values Missing
_embedded.show.dvdCountry has 56 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 55 (98.2%) missing values Missing
_embedded.show.externals.thetvdb has 15 (26.8%) missing values Missing
_embedded.show.externals.imdb has 21 (37.5%) missing values Missing
_embedded.show.image.medium has 4 (7.1%) missing values Missing
_embedded.show.image.original has 4 (7.1%) missing values Missing
_embedded.show.summary has 6 (10.7%) missing values Missing
image has 56 (100.0%) missing values Missing
_embedded.show._links.nextepisode.href has 50 (89.3%) missing values Missing
_embedded.show.network.id has 50 (89.3%) missing values Missing
_embedded.show.network.name has 50 (89.3%) missing values Missing
_embedded.show.network.country.name has 50 (89.3%) missing values Missing
_embedded.show.network.country.code has 50 (89.3%) missing values Missing
_embedded.show.network.country.timezone has 50 (89.3%) missing values Missing
_embedded.show.network.officialSite has 55 (98.2%) missing values Missing
_embedded.show.webChannel has 56 (100.0%) missing values Missing
_embedded.show.image has 56 (100.0%) missing values Missing
_embedded.show.webChannel.country has 56 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 55 (98.2%) missing values Missing
_embedded.show.dvdCountry.code has 55 (98.2%) missing values Missing
_embedded.show.dvdCountry.timezone has 55 (98.2%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.rating.average is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:38:12.100796
Analysis finished2022-09-06 02:38:28.576704
Duration16.48 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2029711.446
Minimum1956338
Maximum2318098
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:28.653585image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1956338
5-th percentile1965553
Q11977297.75
median1981699.5
Q32044187
95-th percentile2240011.75
Maximum2318098
Range361760
Interquartile range (IQR)66889.25

Descriptive statistics

Standard deviation91774.99906
Coefficient of variation (CV)0.04521578632
Kurtosis1.771050666
Mean2029711.446
Median Absolute Deviation (MAD)10419
Skewness1.684405582
Sum113663841
Variance8422650452
MonotonicityNot monotonic
2022-09-05T21:38:28.791032image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22698001
 
1.8%
19563381
 
1.8%
19644461
 
1.8%
19809321
 
1.8%
19702531
 
1.8%
19782611
 
1.8%
19826251
 
1.8%
19826261
 
1.8%
19826271
 
1.8%
19972981
 
1.8%
Other values (46)46
82.1%
ValueCountFrequency (%)
19563381
1.8%
19570671
1.8%
19644461
1.8%
19659221
1.8%
19677551
1.8%
19692271
1.8%
19692471
1.8%
19702531
1.8%
19723081
1.8%
19740491
1.8%
ValueCountFrequency (%)
23180981
1.8%
22698001
1.8%
22559831
1.8%
22346881
1.8%
21955991
1.8%
21785611
1.8%
21761231
1.8%
21659291
1.8%
21389241
1.8%
21168311
1.8%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size576.0 B
https://www.tvmaze.com/episodes/2269800/manaki-1x07-golos-zvera-delo-arhangelskogo-manaka
 
1
https://www.tvmaze.com/episodes/1956338/hero-return-1x09-episode-9
 
1
https://www.tvmaze.com/episodes/1964446/bani-negri-pentru-zile-albe-1x03-socoteala
 
1
https://www.tvmaze.com/episodes/1980932/cuzie-pisma-1x20-kak-sdelat-kaming-aut-stavki-zlo-pocemu-on-ohladel
 
1
https://www.tvmaze.com/episodes/1970253/amore-1x49-truth-will-prevail-12
 
1
Other values (51)
51 

Length

Max length146
Median length100
Mean length84.17857143
Min length61

Characters and Unicode

Total characters4714
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2269800/manaki-1x07-golos-zvera-delo-arhangelskogo-manaka
2nd rowhttps://www.tvmaze.com/episodes/1956338/hero-return-1x09-episode-9
3rd rowhttps://www.tvmaze.com/episodes/1978217/swallowed-star-1x03-episode-3
4th rowhttps://www.tvmaze.com/episodes/2052506/wu-shen-zhu-zai-1x81-episode-81
5th rowhttps://www.tvmaze.com/episodes/2138924/tokyo-joshi-pro-wrestling-2020-12-06-tjpw-fall-tour-20-womm-wrestling-of-my-mind

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2269800/manaki-1x07-golos-zvera-delo-arhangelskogo-manaka1
 
1.8%
https://www.tvmaze.com/episodes/1956338/hero-return-1x09-episode-91
 
1.8%
https://www.tvmaze.com/episodes/1964446/bani-negri-pentru-zile-albe-1x03-socoteala1
 
1.8%
https://www.tvmaze.com/episodes/1980932/cuzie-pisma-1x20-kak-sdelat-kaming-aut-stavki-zlo-pocemu-on-ohladel1
 
1.8%
https://www.tvmaze.com/episodes/1970253/amore-1x49-truth-will-prevail-121
 
1.8%
https://www.tvmaze.com/episodes/1978261/ultra-galaxy-fight-the-absolute-conspiracy-1x03-part-31
 
1.8%
https://www.tvmaze.com/episodes/1982625/pappas-pojkar-1x01-obekvam-striptease-och-en-skrikande-bebis1
 
1.8%
https://www.tvmaze.com/episodes/1982626/pappas-pojkar-1x02-dagsfylla-men-var-ar-festen1
 
1.8%
https://www.tvmaze.com/episodes/1982627/pappas-pojkar-1x03-herman-forsoker-bli-bedragare1
 
1.8%
https://www.tvmaze.com/episodes/1997298/the-george-lucas-talk-show-1x18-episode-xviii-decembyrinth1
 
1.8%
Other values (46)46
82.1%

Length

2022-09-05T21:38:28.914252image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2269800/manaki-1x07-golos-zvera-delo-arhangelskogo-manaka1
 
1.8%
https://www.tvmaze.com/episodes/1956338/hero-return-1x09-episode-91
 
1.8%
https://www.tvmaze.com/episodes/1981696/meisje-van-plezier-3x04-aflevering-41
 
1.8%
https://www.tvmaze.com/episodes/1978217/swallowed-star-1x03-episode-31
 
1.8%
https://www.tvmaze.com/episodes/2052506/wu-shen-zhu-zai-1x81-episode-811
 
1.8%
https://www.tvmaze.com/episodes/2138924/tokyo-joshi-pro-wrestling-2020-12-06-tjpw-fall-tour-20-womm-wrestling-of-my-mind1
 
1.8%
https://www.tvmaze.com/episodes/2012320/mans-diary-2x05-episode-51
 
1.8%
https://www.tvmaze.com/episodes/1957067/atlantic-crossing-1x07-gaven1
 
1.8%
https://www.tvmaze.com/episodes/1977314/stjernestov-1x06-episode-61
 
1.8%
https://www.tvmaze.com/episodes/1974049/love-revolution-1x23-episode-231
 
1.8%
Other values (46)46
82.1%

Most occurring characters

ValueCountFrequency (%)
e390
 
8.3%
-369
 
7.8%
s294
 
6.2%
/280
 
5.9%
t260
 
5.5%
o232
 
4.9%
a229
 
4.9%
i198
 
4.2%
w194
 
4.1%
p182
 
3.9%
Other values (29)2086
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3243
68.8%
Decimal Number654
 
13.9%
Other Punctuation448
 
9.5%
Dash Punctuation369
 
7.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e390
12.0%
s294
 
9.1%
t260
 
8.0%
o232
 
7.2%
a229
 
7.1%
i198
 
6.1%
w194
 
6.0%
p182
 
5.6%
m175
 
5.4%
n115
 
3.5%
Other values (15)974
30.0%
Decimal Number
ValueCountFrequency (%)
1126
19.3%
2110
16.8%
098
15.0%
976
11.6%
651
7.8%
343
 
6.6%
841
 
6.3%
741
 
6.3%
535
 
5.4%
433
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/280
62.5%
.112
 
25.0%
:56
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-369
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3243
68.8%
Common1471
31.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e390
12.0%
s294
 
9.1%
t260
 
8.0%
o232
 
7.2%
a229
 
7.1%
i198
 
6.1%
w194
 
6.0%
p182
 
5.6%
m175
 
5.4%
n115
 
3.5%
Other values (15)974
30.0%
Common
ValueCountFrequency (%)
-369
25.1%
/280
19.0%
1126
 
8.6%
.112
 
7.6%
2110
 
7.5%
098
 
6.7%
976
 
5.2%
:56
 
3.8%
651
 
3.5%
343
 
2.9%
Other values (4)150
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII4714
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e390
 
8.3%
-369
 
7.8%
s294
 
6.2%
/280
 
5.9%
t260
 
5.5%
o232
 
4.9%
a229
 
4.9%
i198
 
4.2%
w194
 
4.1%
p182
 
3.9%
Other values (29)2086
44.3%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size576.0 B
Episode 5
 
2
Голос зверя. Дело архангельского маньяка
 
1
What ¥1,000 Buys You in Japan's No.1 Dollar Store
 
1
"Как сделать каминг-аут?", "Ставки - зло!", "Почему он охладел?"
 
1
Truth Will Prevail (1/2)
 
1
Other values (50)
50 

Length

Max length95
Median length53
Mean length22.48214286
Min length5

Characters and Unicode

Total characters1259
Distinct characters121
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)96.4%

Sample

1st rowГолос зверя. Дело архангельского маньяка
2nd rowEpisode 9
3rd rowEpisode 3
4th rowEpisode 81
5th rowTJPW Fall Tour '20 ~ WOMM (Wrestling Of My Mind) ~

Common Values

ValueCountFrequency (%)
Episode 52
 
3.6%
Голос зверя. Дело архангельского маньяка1
 
1.8%
What ¥1,000 Buys You in Japan's No.1 Dollar Store1
 
1.8%
"Как сделать каминг-аут?", "Ставки - зло!", "Почему он охладел?"1
 
1.8%
Truth Will Prevail (1/2)1
 
1.8%
Part 31
 
1.8%
Obekväm striptease (och en skrikande bebis)1
 
1.8%
Dagsfylla!! Men var är festen?1
 
1.8%
Herman försöker bli bedragare1
 
1.8%
Episode XVIII: DECEMBYRINTH1
 
1.8%
Other values (45)45
80.4%

Length

2022-09-05T21:38:29.022048image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode12
 
5.9%
aflevering8
 
3.9%
4
 
2.0%
53
 
1.5%
63
 
1.5%
of3
 
1.5%
23
 
1.5%
33
 
1.5%
in3
 
1.5%
43
 
1.5%
Other values (154)159
77.9%

Most occurring characters

ValueCountFrequency (%)
148
 
11.8%
e88
 
7.0%
i61
 
4.8%
a51
 
4.1%
r49
 
3.9%
s46
 
3.7%
l39
 
3.1%
n39
 
3.1%
o39
 
3.1%
t33
 
2.6%
Other values (111)666
52.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter814
64.7%
Uppercase Letter178
 
14.1%
Space Separator148
 
11.8%
Decimal Number59
 
4.7%
Other Punctuation40
 
3.2%
Dash Punctuation8
 
0.6%
Close Punctuation4
 
0.3%
Open Punctuation3
 
0.2%
Currency Symbol3
 
0.2%
Math Symbol2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e88
 
10.8%
i61
 
7.5%
a51
 
6.3%
r49
 
6.0%
s46
 
5.7%
l39
 
4.8%
n39
 
4.8%
o39
 
4.8%
t33
 
4.1%
d25
 
3.1%
Other values (48)344
42.3%
Uppercase Letter
ValueCountFrequency (%)
E23
 
12.9%
T15
 
8.4%
A14
 
7.9%
S11
 
6.2%
M10
 
5.6%
W8
 
4.5%
C8
 
4.5%
O7
 
3.9%
G6
 
3.4%
P6
 
3.4%
Other values (25)70
39.3%
Decimal Number
ValueCountFrequency (%)
214
23.7%
011
18.6%
19
15.3%
66
10.2%
45
 
8.5%
34
 
6.8%
93
 
5.1%
53
 
5.1%
72
 
3.4%
82
 
3.4%
Other Punctuation
ValueCountFrequency (%)
,8
20.0%
"6
15.0%
.5
12.5%
:4
10.0%
/4
10.0%
?4
10.0%
#3
 
7.5%
!3
 
7.5%
'2
 
5.0%
@1
 
2.5%
Currency Symbol
ValueCountFrequency (%)
1
33.3%
$1
33.3%
¥1
33.3%
Space Separator
ValueCountFrequency (%)
148
100.0%
Dash Punctuation
ValueCountFrequency (%)
-8
100.0%
Close Punctuation
ValueCountFrequency (%)
)4
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Math Symbol
ValueCountFrequency (%)
~2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin795
63.1%
Common267
 
21.2%
Cyrillic197
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e88
 
11.1%
i61
 
7.7%
a51
 
6.4%
r49
 
6.2%
s46
 
5.8%
l39
 
4.9%
n39
 
4.9%
o39
 
4.9%
t33
 
4.2%
d25
 
3.1%
Other values (44)325
40.9%
Cyrillic
ValueCountFrequency (%)
о22
 
11.2%
а18
 
9.1%
к13
 
6.6%
л12
 
6.1%
е12
 
6.1%
н10
 
5.1%
м9
 
4.6%
и8
 
4.1%
р7
 
3.6%
с7
 
3.6%
Other values (29)79
40.1%
Common
ValueCountFrequency (%)
148
55.4%
214
 
5.2%
011
 
4.1%
19
 
3.4%
-8
 
3.0%
,8
 
3.0%
66
 
2.2%
"6
 
2.2%
.5
 
1.9%
45
 
1.9%
Other values (18)47
 
17.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1051
83.5%
Cyrillic197
 
15.6%
None10
 
0.8%
Currency Symbols1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
 
14.1%
e88
 
8.4%
i61
 
5.8%
a51
 
4.9%
r49
 
4.7%
s46
 
4.4%
l39
 
3.7%
n39
 
3.7%
o39
 
3.7%
t33
 
3.1%
Other values (63)458
43.6%
Cyrillic
ValueCountFrequency (%)
о22
 
11.2%
а18
 
9.1%
к13
 
6.6%
л12
 
6.1%
е12
 
6.1%
н10
 
5.1%
м9
 
4.6%
и8
 
4.1%
р7
 
3.6%
с7
 
3.6%
Other values (29)79
40.1%
None
ValueCountFrequency (%)
ö2
20.0%
ä2
20.0%
å1
10.0%
í1
10.0%
ų1
10.0%
ė1
10.0%
Ž1
10.0%
¥1
10.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct7
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219.0892857
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:29.106161image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)2

Descriptive statistics

Standard deviation629.5324752
Coefficient of variation (CV)2.873406032
Kurtosis4.991799558
Mean219.0892857
Median Absolute Deviation (MAD)1
Skewness2.61028705
Sum12269
Variance396311.1373
MonotonicityNot monotonic
2022-09-05T21:38:29.186607image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
127
48.2%
29
 
16.1%
39
 
16.1%
20206
 
10.7%
53
 
5.4%
481
 
1.8%
141
 
1.8%
ValueCountFrequency (%)
127
48.2%
29
 
16.1%
39
 
16.1%
53
 
5.4%
141
 
1.8%
481
 
1.8%
20206
 
10.7%
ValueCountFrequency (%)
20206
 
10.7%
481
 
1.8%
141
 
1.8%
53
 
5.4%
39
 
16.1%
29
 
16.1%
127
48.2%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct26
Distinct (%)48.1%
Missing2
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean20.90740741
Minimum1
Maximum333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:29.274007image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.65
Q13
median7
Q317.5
95-th percentile60.85
Maximum333
Range332
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation47.49389971
Coefficient of variation (CV)2.271630279
Kurtosis36.37004185
Mean20.90740741
Median Absolute Deviation (MAD)5
Skewness5.636585817
Sum1129
Variance2255.67051
MonotonicityNot monotonic
2022-09-05T21:38:29.373867image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
27
12.5%
36
 
10.7%
75
 
8.9%
54
 
7.1%
63
 
5.4%
43
 
5.4%
13
 
5.4%
492
 
3.6%
422
 
3.6%
82
 
3.6%
Other values (16)17
30.4%
ValueCountFrequency (%)
13
5.4%
27
12.5%
36
10.7%
43
5.4%
54
7.1%
63
5.4%
75
8.9%
82
 
3.6%
91
 
1.8%
102
 
3.6%
ValueCountFrequency (%)
3331
1.8%
851
1.8%
811
1.8%
501
1.8%
492
3.6%
461
1.8%
422
3.6%
361
1.8%
351
1.8%
231
1.8%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size576.0 B
regular
54 
insignificant_special
 
1
significant_special
 
1

Length

Max length21
Median length7
Mean length7.464285714
Min length7

Characters and Unicode

Total characters418
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)3.6%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular54
96.4%
insignificant_special1
 
1.8%
significant_special1
 
1.8%

Length

2022-09-05T21:38:29.472189image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:29.559342image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular54
96.4%
insignificant_special1
 
1.8%
significant_special1
 
1.8%

Most occurring characters

ValueCountFrequency (%)
r108
25.8%
a58
13.9%
e56
13.4%
g56
13.4%
l56
13.4%
u54
12.9%
i9
 
2.2%
n5
 
1.2%
s4
 
1.0%
c4
 
1.0%
Other values (4)8
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter416
99.5%
Connector Punctuation2
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r108
26.0%
a58
13.9%
e56
13.5%
g56
13.5%
l56
13.5%
u54
13.0%
i9
 
2.2%
n5
 
1.2%
s4
 
1.0%
c4
 
1.0%
Other values (3)6
 
1.4%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin416
99.5%
Common2
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
r108
26.0%
a58
13.9%
e56
13.5%
g56
13.5%
l56
13.5%
u54
13.0%
i9
 
2.2%
n5
 
1.2%
s4
 
1.0%
c4
 
1.0%
Other values (3)6
 
1.4%
Common
ValueCountFrequency (%)
_2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII418
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r108
25.8%
a58
13.9%
e56
13.4%
g56
13.4%
l56
13.4%
u54
12.9%
i9
 
2.2%
n5
 
1.2%
s4
 
1.0%
c4
 
1.0%
Other values (4)8
 
1.9%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size576.0 B
2020-12-06
56 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters560
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-06
2nd row2020-12-06
3rd row2020-12-06
4th row2020-12-06
5th row2020-12-06

Common Values

ValueCountFrequency (%)
2020-12-0656
100.0%

Length

2022-09-05T21:38:29.636529image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:29.712580image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-0656
100.0%

Most occurring characters

ValueCountFrequency (%)
2168
30.0%
0168
30.0%
-112
20.0%
156
 
10.0%
656
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number448
80.0%
Dash Punctuation112
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2168
37.5%
0168
37.5%
156
 
12.5%
656
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common560
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2168
30.0%
0168
30.0%
-112
20.0%
156
 
10.0%
656
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2168
30.0%
0168
30.0%
-112
20.0%
156
 
10.0%
656
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size576.0 B
42 
10:00
 
3
12:00
 
3
06:00
 
2
17:00
 
1
Other values (5)

Length

Max length5
Median length0
Mean length1.25
Min length0

Characters and Unicode

Total characters70
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)10.7%

Sample

1st row
2nd row10:00
3rd row10:00
4th row10:00
5th row12:00

Common Values

ValueCountFrequency (%)
42
75.0%
10:003
 
5.4%
12:003
 
5.4%
06:002
 
3.6%
17:001
 
1.8%
18:001
 
1.8%
14:001
 
1.8%
22:201
 
1.8%
19:001
 
1.8%
20:001
 
1.8%

Length

2022-09-05T21:38:29.795083image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:29.922319image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
10:003
21.4%
12:003
21.4%
06:002
14.3%
17:001
 
7.1%
18:001
 
7.1%
14:001
 
7.1%
22:201
 
7.1%
19:001
 
7.1%
20:001
 
7.1%

Most occurring characters

ValueCountFrequency (%)
033
47.1%
:14
20.0%
110
 
14.3%
27
 
10.0%
62
 
2.9%
71
 
1.4%
81
 
1.4%
41
 
1.4%
91
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number56
80.0%
Other Punctuation14
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
033
58.9%
110
 
17.9%
27
 
12.5%
62
 
3.6%
71
 
1.8%
81
 
1.8%
41
 
1.8%
91
 
1.8%
Other Punctuation
ValueCountFrequency (%)
:14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common70
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
033
47.1%
:14
20.0%
110
 
14.3%
27
 
10.0%
62
 
2.9%
71
 
1.4%
81
 
1.4%
41
 
1.4%
91
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII70
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
033
47.1%
:14
20.0%
110
 
14.3%
27
 
10.0%
62
 
2.9%
71
 
1.4%
81
 
1.4%
41
 
1.4%
91
 
1.4%

airstamp
Categorical

HIGH CORRELATION

Distinct14
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size576.0 B
2020-12-06T12:00:00+00:00
21 
2020-12-06T11:00:00+00:00
15 
2020-12-06T17:00:00+00:00
2020-12-06T02:00:00+00:00
2020-12-06T05:00:00+00:00
 
2
Other values (9)

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1400
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)16.1%

Sample

1st row2020-12-06T00:00:00+00:00
2nd row2020-12-06T02:00:00+00:00
3rd row2020-12-06T02:00:00+00:00
4th row2020-12-06T02:00:00+00:00
5th row2020-12-06T03:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-06T12:00:00+00:0021
37.5%
2020-12-06T11:00:00+00:0015
26.8%
2020-12-06T17:00:00+00:006
 
10.7%
2020-12-06T02:00:00+00:003
 
5.4%
2020-12-06T05:00:00+00:002
 
3.6%
2020-12-06T00:00:00+00:001
 
1.8%
2020-12-06T03:00:00+00:001
 
1.8%
2020-12-06T04:00:00+00:001
 
1.8%
2020-12-06T08:00:00+00:001
 
1.8%
2020-12-06T09:00:00+00:001
 
1.8%
Other values (4)4
 
7.1%

Length

2022-09-05T21:38:30.011630image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-06t12:00:00+00:0021
37.5%
2020-12-06t11:00:00+00:0015
26.8%
2020-12-06t17:00:00+00:006
 
10.7%
2020-12-06t02:00:00+00:003
 
5.4%
2020-12-06t05:00:00+00:002
 
3.6%
2020-12-06t00:00:00+00:001
 
1.8%
2020-12-06t03:00:00+00:001
 
1.8%
2020-12-06t04:00:00+00:001
 
1.8%
2020-12-06t08:00:00+00:001
 
1.8%
2020-12-06t09:00:00+00:001
 
1.8%
Other values (4)4
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0629
44.9%
2194
 
13.9%
:168
 
12.0%
1116
 
8.3%
-112
 
8.0%
T56
 
4.0%
+56
 
4.0%
654
 
3.9%
78
 
0.6%
52
 
0.1%
Other values (4)5
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1008
72.0%
Other Punctuation168
 
12.0%
Dash Punctuation112
 
8.0%
Uppercase Letter56
 
4.0%
Math Symbol56
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0629
62.4%
2194
 
19.2%
1116
 
11.5%
654
 
5.4%
78
 
0.8%
52
 
0.2%
42
 
0.2%
31
 
0.1%
81
 
0.1%
91
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:168
100.0%
Dash Punctuation
ValueCountFrequency (%)
-112
100.0%
Uppercase Letter
ValueCountFrequency (%)
T56
100.0%
Math Symbol
ValueCountFrequency (%)
+56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1344
96.0%
Latin56
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0629
46.8%
2194
 
14.4%
:168
 
12.5%
1116
 
8.6%
-112
 
8.3%
+56
 
4.2%
654
 
4.0%
78
 
0.6%
52
 
0.1%
42
 
0.1%
Other values (3)3
 
0.2%
Latin
ValueCountFrequency (%)
T56
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0629
44.9%
2194
 
13.9%
:168
 
12.0%
1116
 
8.3%
-112
 
8.0%
T56
 
4.0%
+56
 
4.0%
654
 
3.9%
78
 
0.6%
52
 
0.1%
Other values (4)5
 
0.4%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct27
Distinct (%)54.0%
Missing6
Missing (%)10.7%
Infinite0
Infinite (%)0.0%
Mean47.74
Minimum5
Maximum188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:30.102319image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile10.9
Q122
median43.5
Q345
95-th percentile120
Maximum188
Range183
Interquartile range (IQR)23

Descriptive statistics

Standard deviation39.49001941
Coefficient of variation (CV)0.8271893466
Kurtosis4.591702338
Mean47.74
Median Absolute Deviation (MAD)16.5
Skewness2.086217074
Sum2387
Variance1559.461633
MonotonicityNot monotonic
2022-09-05T21:38:30.208895image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
4511
19.6%
1204
 
7.1%
153
 
5.4%
603
 
5.4%
223
 
5.4%
402
 
3.6%
422
 
3.6%
442
 
3.6%
302
 
3.6%
631
 
1.8%
Other values (17)17
30.4%
(Missing)6
 
10.7%
ValueCountFrequency (%)
51
 
1.8%
81
 
1.8%
101
 
1.8%
121
 
1.8%
141
 
1.8%
153
5.4%
181
 
1.8%
201
 
1.8%
211
 
1.8%
223
5.4%
ValueCountFrequency (%)
1881
 
1.8%
1801
 
1.8%
1204
 
7.1%
631
 
1.8%
621
 
1.8%
603
 
5.4%
541
 
1.8%
4511
19.6%
442
 
3.6%
431
 
1.8%

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct10
Distinct (%)100.0%
Missing46
Missing (%)82.1%
Memory size576.0 B
<p>Märtha ends up in a quandary when the president announces that he wants to support Norway and asks her to say how she feels about him.</p>
<p>When a local teenager suddenly disappears, Elena explores Father Vergara's possible connection. As more untimely deaths befall the town, Marquess Roque presents Elena with an enticing job offer, and Merche urges Paco to keep his distance.</p>
<p>Monica follows up a lead given to her at a party, visiting the co-workers of a man they describe as a pervert.</p>
<p>As the death toll rises, THE GEORGE LUCAS TALK SHOW continues to deliver quality livestream content from the digital safety of PLANET SCUM. Retired filmmaker GEORGE LUCAS (notoriously dead-eyed character actor CONNOR RATLIFF) and his CGI co-host WATTO (GRIFFIN NEWMAN, co-lead on Amazon's THE TICK) welcome guests and have fun while actively NOT spreading a disease. They are joined, as always, by snack-snacking, nap-napping producer PATRICK COTNOIR (aka Nickname Jokenoir) whose druthers include you following him on twitter RIGHT NOW: @patrickcotnoir Only a few weeks left in 2020. Who knows what fresh hell awaits us in 2021? Dot dot dot dot..</p>
Other values (5)

Length

Max length654
Median length239
Mean length248
Min length0

Characters and Unicode

Total characters2480
Distinct characters73
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row
2nd row<p>Märtha ends up in a quandary when the president announces that he wants to support Norway and asks her to say how she feels about him.</p>
3rd row<p>When a local teenager suddenly disappears, Elena explores Father Vergara's possible connection. As more untimely deaths befall the town, Marquess Roque presents Elena with an enticing job offer, and Merche urges Paco to keep his distance.</p>
4th row<p>Monica follows up a lead given to her at a party, visiting the co-workers of a man they describe as a pervert.</p>
5th row<p>As the death toll rises, THE GEORGE LUCAS TALK SHOW continues to deliver quality livestream content from the digital safety of PLANET SCUM. Retired filmmaker GEORGE LUCAS (notoriously dead-eyed character actor CONNOR RATLIFF) and his CGI co-host WATTO (GRIFFIN NEWMAN, co-lead on Amazon's THE TICK) welcome guests and have fun while actively NOT spreading a disease. They are joined, as always, by snack-snacking, nap-napping producer PATRICK COTNOIR (aka Nickname Jokenoir) whose druthers include you following him on twitter RIGHT NOW: @patrickcotnoir Only a few weeks left in 2020. Who knows what fresh hell awaits us in 2021? Dot dot dot dot..</p>

Common Values

ValueCountFrequency (%)
1
 
1.8%
<p>Märtha ends up in a quandary when the president announces that he wants to support Norway and asks her to say how she feels about him.</p>1
 
1.8%
<p>When a local teenager suddenly disappears, Elena explores Father Vergara's possible connection. As more untimely deaths befall the town, Marquess Roque presents Elena with an enticing job offer, and Merche urges Paco to keep his distance.</p>1
 
1.8%
<p>Monica follows up a lead given to her at a party, visiting the co-workers of a man they describe as a pervert.</p>1
 
1.8%
<p>As the death toll rises, THE GEORGE LUCAS TALK SHOW continues to deliver quality livestream content from the digital safety of PLANET SCUM. Retired filmmaker GEORGE LUCAS (notoriously dead-eyed character actor CONNOR RATLIFF) and his CGI co-host WATTO (GRIFFIN NEWMAN, co-lead on Amazon's THE TICK) welcome guests and have fun while actively NOT spreading a disease. They are joined, as always, by snack-snacking, nap-napping producer PATRICK COTNOIR (aka Nickname Jokenoir) whose druthers include you following him on twitter RIGHT NOW: @patrickcotnoir Only a few weeks left in 2020. Who knows what fresh hell awaits us in 2021? Dot dot dot dot..</p>1
 
1.8%
<p>Ghost Dimension's Bex and Sean investigate Chillingham Castle for a Halloween investigation. The most haunted castle in the world. Reports of paranormal activity are daily here, so what will the team manage to capture tonight? as they prepare to spend the night with the ghosts.</p>1
 
1.8%
<p>The crew escaped, barely to the Wistful Wish, while their squiggly pursuers decide to fight instead of flee, and well…see how it worked out for them. Incidents on board also let us see snippets of Ilay &amp; Cycla-919's pasts.</p>1
 
1.8%
<p>Truths come out and accusations fly when members of the TikTok creator mansion turn against one of their own, proving it's every person for themselves.</p>1
 
1.8%
<p>IDOLiSH7 is accused of appropriating Zero's songs, so Takanashi Production holds a press conference. Nagi volunteers to face the press and explains that he was officially given the rights to the song by composer Sakura Haruki. However, a suspicious man dressed as Zero appears at the press conference, aggravating the scandal.</p>1
 
1.8%
<p>On a journey to find love, Chance invites 15 beautiful "ladies" into his home. Each week he will put the hopefuls through various challenges to test their compatibility among other things. However, with constant infighting between the contestants, will Chance be able to finally find his happily ever after?</p>1
 
1.8%
(Missing)46
82.1%

Length

2022-09-05T21:38:30.311153image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:30.431817image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
the21
 
5.3%
to14
 
3.6%
a12
 
3.0%
and8
 
2.0%
of8
 
2.0%
as5
 
1.3%
in4
 
1.0%
his4
 
1.0%
press3
 
0.8%
for3
 
0.8%
Other values (275)312
79.2%

Most occurring characters

ValueCountFrequency (%)
385
15.5%
e220
 
8.9%
a158
 
6.4%
t153
 
6.2%
s138
 
5.6%
o134
 
5.4%
n126
 
5.1%
i121
 
4.9%
r101
 
4.1%
h93
 
3.8%
Other values (63)851
34.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1799
72.5%
Space Separator385
 
15.5%
Uppercase Letter168
 
6.8%
Other Punctuation65
 
2.6%
Math Symbol36
 
1.5%
Decimal Number14
 
0.6%
Dash Punctuation7
 
0.3%
Open Punctuation3
 
0.1%
Close Punctuation3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e220
12.2%
a158
 
8.8%
t153
 
8.5%
s138
 
7.7%
o134
 
7.4%
n126
 
7.0%
i121
 
6.7%
r101
 
5.6%
h93
 
5.2%
l79
 
4.4%
Other values (17)476
26.5%
Uppercase Letter
ValueCountFrequency (%)
T19
 
11.3%
C13
 
7.7%
O13
 
7.7%
N12
 
7.1%
E11
 
6.5%
I11
 
6.5%
A11
 
6.5%
R11
 
6.5%
H9
 
5.4%
W8
 
4.8%
Other values (13)50
29.8%
Other Punctuation
ValueCountFrequency (%)
,20
30.8%
.20
30.8%
/9
13.8%
'6
 
9.2%
?3
 
4.6%
"2
 
3.1%
:1
 
1.5%
1
 
1.5%
&1
 
1.5%
;1
 
1.5%
Decimal Number
ValueCountFrequency (%)
24
28.6%
03
21.4%
13
21.4%
92
14.3%
71
 
7.1%
51
 
7.1%
Math Symbol
ValueCountFrequency (%)
<18
50.0%
>18
50.0%
Space Separator
ValueCountFrequency (%)
385
100.0%
Dash Punctuation
ValueCountFrequency (%)
-7
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1967
79.3%
Common513
 
20.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e220
 
11.2%
a158
 
8.0%
t153
 
7.8%
s138
 
7.0%
o134
 
6.8%
n126
 
6.4%
i121
 
6.2%
r101
 
5.1%
h93
 
4.7%
l79
 
4.0%
Other values (40)644
32.7%
Common
ValueCountFrequency (%)
385
75.0%
,20
 
3.9%
.20
 
3.9%
<18
 
3.5%
>18
 
3.5%
/9
 
1.8%
-7
 
1.4%
'6
 
1.2%
24
 
0.8%
03
 
0.6%
Other values (13)23
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2478
99.9%
Punctuation1
 
< 0.1%
None1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
385
15.5%
e220
 
8.9%
a158
 
6.4%
t153
 
6.2%
s138
 
5.6%
o134
 
5.4%
n126
 
5.1%
i121
 
4.9%
r101
 
4.1%
h93
 
3.8%
Other values (61)849
34.3%
Punctuation
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
ä1
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing53
Missing (%)94.6%
Memory size576.0 B
8.3
9.0
8.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row8.3
2nd row9.0
3rd row8.0

Common Values

ValueCountFrequency (%)
8.31
 
1.8%
9.01
 
1.8%
8.01
 
1.8%
(Missing)53
94.6%

Length

2022-09-05T21:38:30.574815image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:30.658715image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
8.31
33.3%
9.01
33.3%
8.01
33.3%

Most occurring characters

ValueCountFrequency (%)
.3
33.3%
82
22.2%
02
22.2%
31
 
11.1%
91
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
66.7%
Other Punctuation3
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
82
33.3%
02
33.3%
31
16.7%
91
16.7%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.3
33.3%
82
22.2%
02
22.2%
31
 
11.1%
91
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.3
33.3%
82
22.2%
02
22.2%
31
 
11.1%
91
 
11.1%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct20
Distinct (%)100.0%
Missing36
Missing (%)64.3%
Memory size576.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/394/985941.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/287/719274.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/285/714231.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/389/973508.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/292/730200.jpg
 
1
Other values (15)
15 

Length

Max length73
Median length72
Mean length72.05
Min length72

Characters and Unicode

Total characters1441
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/394/985941.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/284/711894.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726340.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/719267.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/719268.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/394/985941.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719274.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/285/714231.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/389/973508.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/292/730200.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/287/717640.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/310/776219.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/287/717618.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719085.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/401/1003921.jpg1
 
1.8%
Other values (10)10
 
17.9%
(Missing)36
64.3%

Length

2022-09-05T21:38:30.743186image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/394/985941.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719274.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/medium_landscape/284/711894.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726340.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719267.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719268.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719269.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719270.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719271.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719272.jpg1
 
5.0%
Other values (10)10
50.0%

Most occurring characters

ValueCountFrequency (%)
/140
 
9.7%
a120
 
8.3%
t100
 
6.9%
s100
 
6.9%
m100
 
6.9%
p80
 
5.6%
e80
 
5.6%
i60
 
4.2%
c60
 
4.2%
.60
 
4.2%
Other values (22)541
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1020
70.8%
Other Punctuation220
 
15.3%
Decimal Number181
 
12.6%
Connector Punctuation20
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a120
11.8%
t100
9.8%
s100
9.8%
m100
9.8%
p80
 
7.8%
e80
 
7.8%
i60
 
5.9%
c60
 
5.9%
d60
 
5.9%
l40
 
3.9%
Other values (8)220
21.6%
Decimal Number
ValueCountFrequency (%)
737
20.4%
231
17.1%
123
12.7%
922
12.2%
822
12.2%
013
 
7.2%
311
 
6.1%
49
 
5.0%
67
 
3.9%
56
 
3.3%
Other Punctuation
ValueCountFrequency (%)
/140
63.6%
.60
27.3%
:20
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1020
70.8%
Common421
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a120
11.8%
t100
9.8%
s100
9.8%
m100
9.8%
p80
 
7.8%
e80
 
7.8%
i60
 
5.9%
c60
 
5.9%
d60
 
5.9%
l40
 
3.9%
Other values (8)220
21.6%
Common
ValueCountFrequency (%)
/140
33.3%
.60
14.3%
737
 
8.8%
231
 
7.4%
123
 
5.5%
922
 
5.2%
822
 
5.2%
_20
 
4.8%
:20
 
4.8%
013
 
3.1%
Other values (4)33
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII1441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/140
 
9.7%
a120
 
8.3%
t100
 
6.9%
s100
 
6.9%
m100
 
6.9%
p80
 
5.6%
e80
 
5.6%
i60
 
4.2%
c60
 
4.2%
.60
 
4.2%
Other values (22)541
37.5%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct20
Distinct (%)100.0%
Missing36
Missing (%)64.3%
Memory size576.0 B
https://static.tvmaze.com/uploads/images/original_untouched/394/985941.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/287/719274.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/285/714231.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/389/973508.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/292/730200.jpg
 
1
Other values (15)
15 

Length

Max length75
Median length74
Mean length74.05
Min length74

Characters and Unicode

Total characters1481
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/394/985941.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/284/711894.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726340.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719267.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719268.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/394/985941.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/287/719274.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/714231.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/389/973508.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/292/730200.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/287/717640.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/310/776219.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/287/717618.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/287/719085.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/401/1003921.jpg1
 
1.8%
Other values (10)10
 
17.9%
(Missing)36
64.3%

Length

2022-09-05T21:38:30.838553image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/394/985941.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/719274.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/284/711894.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726340.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/719267.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/719268.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/719269.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/719270.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/719271.jpg1
 
5.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/719272.jpg1
 
5.0%
Other values (10)10
50.0%

Most occurring characters

ValueCountFrequency (%)
/140
 
9.5%
t120
 
8.1%
a100
 
6.8%
s80
 
5.4%
i80
 
5.4%
o80
 
5.4%
p60
 
4.1%
c60
 
4.1%
.60
 
4.1%
g60
 
4.1%
Other values (23)641
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1060
71.6%
Other Punctuation220
 
14.9%
Decimal Number181
 
12.2%
Connector Punctuation20
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t120
 
11.3%
a100
 
9.4%
s80
 
7.5%
i80
 
7.5%
o80
 
7.5%
p60
 
5.7%
c60
 
5.7%
g60
 
5.7%
m60
 
5.7%
e60
 
5.7%
Other values (9)300
28.3%
Decimal Number
ValueCountFrequency (%)
737
20.4%
231
17.1%
123
12.7%
922
12.2%
822
12.2%
013
 
7.2%
311
 
6.1%
49
 
5.0%
67
 
3.9%
56
 
3.3%
Other Punctuation
ValueCountFrequency (%)
/140
63.6%
.60
27.3%
:20
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1060
71.6%
Common421
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t120
 
11.3%
a100
 
9.4%
s80
 
7.5%
i80
 
7.5%
o80
 
7.5%
p60
 
5.7%
c60
 
5.7%
g60
 
5.7%
m60
 
5.7%
e60
 
5.7%
Other values (9)300
28.3%
Common
ValueCountFrequency (%)
/140
33.3%
.60
14.3%
737
 
8.8%
231
 
7.4%
123
 
5.5%
922
 
5.2%
822
 
5.2%
:20
 
4.8%
_20
 
4.8%
013
 
3.1%
Other values (4)33
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII1481
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/140
 
9.5%
t120
 
8.1%
a100
 
6.8%
s80
 
5.4%
i80
 
5.4%
o80
 
5.4%
p60
 
4.1%
c60
 
4.1%
.60
 
4.1%
g60
 
4.1%
Other values (23)641
43.3%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size576.0 B
https://api.tvmaze.com/episodes/2269800
 
1
https://api.tvmaze.com/episodes/1956338
 
1
https://api.tvmaze.com/episodes/1964446
 
1
https://api.tvmaze.com/episodes/1980932
 
1
https://api.tvmaze.com/episodes/1970253
 
1
Other values (51)
51 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2184
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2269800
2nd rowhttps://api.tvmaze.com/episodes/1956338
3rd rowhttps://api.tvmaze.com/episodes/1978217
4th rowhttps://api.tvmaze.com/episodes/2052506
5th rowhttps://api.tvmaze.com/episodes/2138924

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/22698001
 
1.8%
https://api.tvmaze.com/episodes/19563381
 
1.8%
https://api.tvmaze.com/episodes/19644461
 
1.8%
https://api.tvmaze.com/episodes/19809321
 
1.8%
https://api.tvmaze.com/episodes/19702531
 
1.8%
https://api.tvmaze.com/episodes/19782611
 
1.8%
https://api.tvmaze.com/episodes/19826251
 
1.8%
https://api.tvmaze.com/episodes/19826261
 
1.8%
https://api.tvmaze.com/episodes/19826271
 
1.8%
https://api.tvmaze.com/episodes/19972981
 
1.8%
Other values (46)46
82.1%

Length

2022-09-05T21:38:30.926427image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/22698001
 
1.8%
https://api.tvmaze.com/episodes/19563381
 
1.8%
https://api.tvmaze.com/episodes/19816961
 
1.8%
https://api.tvmaze.com/episodes/19782171
 
1.8%
https://api.tvmaze.com/episodes/20525061
 
1.8%
https://api.tvmaze.com/episodes/21389241
 
1.8%
https://api.tvmaze.com/episodes/20123201
 
1.8%
https://api.tvmaze.com/episodes/19570671
 
1.8%
https://api.tvmaze.com/episodes/19773141
 
1.8%
https://api.tvmaze.com/episodes/19740491
 
1.8%
Other values (46)46
82.1%

Most occurring characters

ValueCountFrequency (%)
/224
 
10.3%
p168
 
7.7%
s168
 
7.7%
e168
 
7.7%
t168
 
7.7%
a112
 
5.1%
i112
 
5.1%
.112
 
5.1%
m112
 
5.1%
o112
 
5.1%
Other values (16)728
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1400
64.1%
Other Punctuation392
 
17.9%
Decimal Number392
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p168
12.0%
s168
12.0%
e168
12.0%
t168
12.0%
a112
8.0%
i112
8.0%
m112
8.0%
o112
8.0%
h56
 
4.0%
d56
 
4.0%
Other values (3)168
12.0%
Decimal Number
ValueCountFrequency (%)
172
18.4%
970
17.9%
257
14.5%
634
8.7%
834
8.7%
734
8.7%
030
7.7%
524
 
6.1%
319
 
4.8%
418
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/224
57.1%
.112
28.6%
:56
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1400
64.1%
Common784
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/224
28.6%
.112
14.3%
172
 
9.2%
970
 
8.9%
257
 
7.3%
:56
 
7.1%
634
 
4.3%
834
 
4.3%
734
 
4.3%
030
 
3.8%
Other values (3)61
 
7.8%
Latin
ValueCountFrequency (%)
p168
12.0%
s168
12.0%
e168
12.0%
t168
12.0%
a112
8.0%
i112
8.0%
m112
8.0%
o112
8.0%
h56
 
4.0%
d56
 
4.0%
Other values (3)168
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/224
 
10.3%
p168
 
7.7%
s168
 
7.7%
e168
 
7.7%
t168
 
7.7%
a112
 
5.1%
i112
 
5.1%
.112
 
5.1%
m112
 
5.1%
o112
 
5.1%
Other values (16)728
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct45
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43886.19643
Minimum2266
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:31.022001image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2266
5-th percentile21857.75
Q133039.75
median49844
Q352370
95-th percentile58616.5
Maximum61755
Range59489
Interquartile range (IQR)19330.25

Descriptive statistics

Standard deviation12959.54443
Coefficient of variation (CV)0.2952988749
Kurtosis1.24527437
Mean43886.19643
Median Absolute Deviation (MAD)6389.5
Skewness-1.177620223
Sum2457627
Variance167949791.8
MonotonicityNot monotonic
2022-09-05T21:38:31.129751image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
317708
 
14.3%
523033
 
5.4%
349402
 
3.6%
525712
 
3.6%
485971
 
1.8%
583561
 
1.8%
527371
 
1.8%
528581
 
1.8%
533381
 
1.8%
538901
 
1.8%
Other values (35)35
62.5%
ValueCountFrequency (%)
22661
 
1.8%
75911
 
1.8%
187521
 
1.8%
228931
 
1.8%
249631
 
1.8%
306061
 
1.8%
317708
14.3%
334631
 
1.8%
349402
 
3.6%
369071
 
1.8%
ValueCountFrequency (%)
617551
1.8%
599511
1.8%
593981
1.8%
583561
1.8%
578741
1.8%
559861
1.8%
547891
1.8%
540331
1.8%
538901
1.8%
533381
1.8%

_embedded.show.url
Categorical

HIGH CORRELATION

Distinct45
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size576.0 B
https://www.tvmaze.com/shows/31770/meisje-van-plezier
https://www.tvmaze.com/shows/52303/pappas-pojkar
 
3
https://www.tvmaze.com/shows/34940/fancy-nancy
 
2
https://www.tvmaze.com/shows/52571/lassemajas-detektivbyra
 
2
https://www.tvmaze.com/shows/48597/manaki
 
1
Other values (40)
40 

Length

Max length77
Median length60
Mean length50.875
Min length40

Characters and Unicode

Total characters2849
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)73.2%

Sample

1st rowhttps://www.tvmaze.com/shows/48597/manaki
2nd rowhttps://www.tvmaze.com/shows/51471/hero-return
3rd rowhttps://www.tvmaze.com/shows/52178/swallowed-star
4th rowhttps://www.tvmaze.com/shows/54033/wu-shen-zhu-zai
5th rowhttps://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestling

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/31770/meisje-van-plezier8
 
14.3%
https://www.tvmaze.com/shows/52303/pappas-pojkar3
 
5.4%
https://www.tvmaze.com/shows/34940/fancy-nancy2
 
3.6%
https://www.tvmaze.com/shows/52571/lassemajas-detektivbyra2
 
3.6%
https://www.tvmaze.com/shows/48597/manaki1
 
1.8%
https://www.tvmaze.com/shows/58356/into-the-mother-lands1
 
1.8%
https://www.tvmaze.com/shows/52737/the-george-lucas-talk-show1
 
1.8%
https://www.tvmaze.com/shows/52858/laikykites-ten1
 
1.8%
https://www.tvmaze.com/shows/53338/el-anesa-farah1
 
1.8%
https://www.tvmaze.com/shows/53890/ghost-dimension-lock-down1
 
1.8%
Other values (35)35
62.5%

Length

2022-09-05T21:38:31.238167image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/31770/meisje-van-plezier8
 
14.3%
https://www.tvmaze.com/shows/52303/pappas-pojkar3
 
5.4%
https://www.tvmaze.com/shows/34940/fancy-nancy2
 
3.6%
https://www.tvmaze.com/shows/52571/lassemajas-detektivbyra2
 
3.6%
https://www.tvmaze.com/shows/51812/norge-i-krise1
 
1.8%
https://www.tvmaze.com/shows/52178/swallowed-star1
 
1.8%
https://www.tvmaze.com/shows/54033/wu-shen-zhu-zai1
 
1.8%
https://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestling1
 
1.8%
https://www.tvmaze.com/shows/50398/mans-diary1
 
1.8%
https://www.tvmaze.com/shows/44659/atlantic-crossing1
 
1.8%
Other values (35)35
62.5%

Most occurring characters

ValueCountFrequency (%)
/280
 
9.8%
w240
 
8.4%
s223
 
7.8%
t208
 
7.3%
o162
 
5.7%
e151
 
5.3%
m139
 
4.9%
a135
 
4.7%
h131
 
4.6%
.112
 
3.9%
Other values (29)1068
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2024
71.0%
Other Punctuation448
 
15.7%
Decimal Number284
 
10.0%
Dash Punctuation93
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w240
11.9%
s223
11.0%
t208
10.3%
o162
 
8.0%
e151
 
7.5%
m139
 
6.9%
a135
 
6.7%
h131
 
6.5%
p90
 
4.4%
c77
 
3.8%
Other values (15)468
23.1%
Decimal Number
ValueCountFrequency (%)
341
14.4%
541
14.4%
735
12.3%
431
10.9%
127
9.5%
927
9.5%
225
8.8%
024
8.5%
820
7.0%
613
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/280
62.5%
.112
 
25.0%
:56
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2024
71.0%
Common825
29.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w240
11.9%
s223
11.0%
t208
10.3%
o162
 
8.0%
e151
 
7.5%
m139
 
6.9%
a135
 
6.7%
h131
 
6.5%
p90
 
4.4%
c77
 
3.8%
Other values (15)468
23.1%
Common
ValueCountFrequency (%)
/280
33.9%
.112
 
13.6%
-93
 
11.3%
:56
 
6.8%
341
 
5.0%
541
 
5.0%
735
 
4.2%
431
 
3.8%
127
 
3.3%
927
 
3.3%
Other values (4)82
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII2849
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/280
 
9.8%
w240
 
8.4%
s223
 
7.8%
t208
 
7.3%
o162
 
5.7%
e151
 
5.3%
m139
 
4.9%
a135
 
4.7%
h131
 
4.6%
.112
 
3.9%
Other values (29)1068
37.5%

_embedded.show.name
Categorical

HIGH CORRELATION

Distinct45
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size576.0 B
Meisje van Plezier
Pappas pojkar
 
3
Fancy Nancy
 
2
LasseMajas Detektivbyrå
 
2
Маньяки
 
1
Other values (40)
40 

Length

Max length43
Median length23
Mean length16.19642857
Min length5

Characters and Unicode

Total characters907
Distinct characters91
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)73.2%

Sample

1st rowМаньяки
2nd rowHero Return
3rd rowSwallowed Star
4th rowWu Shen Zhu Zai
5th rowTokyo Joshi Pro Wrestling

Common Values

ValueCountFrequency (%)
Meisje van Plezier8
 
14.3%
Pappas pojkar3
 
5.4%
Fancy Nancy2
 
3.6%
LasseMajas Detektivbyrå2
 
3.6%
Маньяки1
 
1.8%
Into the Mother Lands1
 
1.8%
The George Lucas Talk Show1
 
1.8%
Laikykitės Ten1
 
1.8%
El Anesa Farah1
 
1.8%
Ghost Dimension Lock Down1
 
1.8%
Other values (35)35
62.5%

Length

2022-09-05T21:38:31.348809image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
meisje8
 
5.4%
plezier8
 
5.4%
van8
 
5.4%
pojkar3
 
2.0%
the3
 
2.0%
pappas3
 
2.0%
nancy2
 
1.3%
wrestling2
 
1.3%
wwe2
 
1.3%
fancy2
 
1.3%
Other values (104)108
72.5%

Most occurring characters

ValueCountFrequency (%)
93
 
10.3%
e89
 
9.8%
a60
 
6.6%
i55
 
6.1%
n53
 
5.8%
r45
 
5.0%
s44
 
4.9%
o41
 
4.5%
t29
 
3.2%
l27
 
3.0%
Other values (81)371
40.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter654
72.1%
Uppercase Letter140
 
15.4%
Space Separator93
 
10.3%
Other Punctuation9
 
1.0%
Decimal Number6
 
0.7%
Close Punctuation2
 
0.2%
Currency Symbol2
 
0.2%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e89
13.6%
a60
 
9.2%
i55
 
8.4%
n53
 
8.1%
r45
 
6.9%
s44
 
6.7%
o41
 
6.3%
t29
 
4.4%
l27
 
4.1%
p18
 
2.8%
Other values (39)193
29.5%
Uppercase Letter
ValueCountFrequency (%)
M16
 
11.4%
P15
 
10.7%
T11
 
7.9%
W9
 
6.4%
S9
 
6.4%
D8
 
5.7%
A8
 
5.7%
L8
 
5.7%
F7
 
5.0%
N6
 
4.3%
Other values (17)43
30.7%
Other Punctuation
ValueCountFrequency (%)
'5
55.6%
#1
 
11.1%
@1
 
11.1%
?1
 
11.1%
:1
 
11.1%
Decimal Number
ValueCountFrequency (%)
02
33.3%
41
16.7%
21
16.7%
31
16.7%
71
16.7%
Currency Symbol
ValueCountFrequency (%)
1
50.0%
$1
50.0%
Space Separator
ValueCountFrequency (%)
93
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin755
83.2%
Common113
 
12.5%
Cyrillic39
 
4.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e89
 
11.8%
a60
 
7.9%
i55
 
7.3%
n53
 
7.0%
r45
 
6.0%
s44
 
5.8%
o41
 
5.4%
t29
 
3.8%
l27
 
3.6%
p18
 
2.4%
Other values (43)294
38.9%
Cyrillic
ValueCountFrequency (%)
и4
 
10.3%
а4
 
10.3%
к3
 
7.7%
м3
 
7.7%
о2
 
5.1%
е2
 
5.1%
у2
 
5.1%
я2
 
5.1%
М2
 
5.1%
ь2
 
5.1%
Other values (13)13
33.3%
Common
ValueCountFrequency (%)
93
82.3%
'5
 
4.4%
02
 
1.8%
)2
 
1.8%
41
 
0.9%
#1
 
0.9%
@1
 
0.9%
1
 
0.9%
?1
 
0.9%
$1
 
0.9%
Other values (5)5
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII859
94.7%
Cyrillic39
 
4.3%
None8
 
0.9%
Currency Symbols1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
93
 
10.8%
e89
 
10.4%
a60
 
7.0%
i55
 
6.4%
n53
 
6.2%
r45
 
5.2%
s44
 
5.1%
o41
 
4.8%
t29
 
3.4%
l27
 
3.1%
Other values (52)323
37.6%
Cyrillic
ValueCountFrequency (%)
и4
 
10.3%
а4
 
10.3%
к3
 
7.7%
м3
 
7.7%
о2
 
5.1%
е2
 
5.1%
у2
 
5.1%
я2
 
5.1%
М2
 
5.1%
ь2
 
5.1%
Other values (13)13
33.3%
None
ValueCountFrequency (%)
å3
37.5%
á2
25.0%
ö1
 
12.5%
ø1
 
12.5%
ė1
 
12.5%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size576.0 B
Scripted
26 
Documentary
Animation
Sports
Talk Show
Other values (3)

Length

Max length11
Median length9
Mean length8.232142857
Min length4

Characters and Unicode

Total characters461
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st rowDocumentary
2nd rowAnimation
3rd rowAnimation
4th rowAnimation
5th rowSports

Common Values

ValueCountFrequency (%)
Scripted26
46.4%
Documentary7
 
12.5%
Animation7
 
12.5%
Sports5
 
8.9%
Talk Show5
 
8.9%
Reality3
 
5.4%
News2
 
3.6%
Game Show1
 
1.8%

Length

2022-09-05T21:38:31.448122image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:31.555534image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted26
41.9%
documentary7
 
11.3%
animation7
 
11.3%
show6
 
9.7%
sports5
 
8.1%
talk5
 
8.1%
reality3
 
4.8%
news2
 
3.2%
game1
 
1.6%

Most occurring characters

ValueCountFrequency (%)
t48
10.4%
i43
 
9.3%
e39
 
8.5%
r38
 
8.2%
S37
 
8.0%
c33
 
7.2%
p31
 
6.7%
d26
 
5.6%
o25
 
5.4%
a23
 
5.0%
Other values (16)118
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter393
85.2%
Uppercase Letter62
 
13.4%
Space Separator6
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t48
12.2%
i43
10.9%
e39
9.9%
r38
9.7%
c33
8.4%
p31
7.9%
d26
 
6.6%
o25
 
6.4%
a23
 
5.9%
n21
 
5.3%
Other values (8)66
16.8%
Uppercase Letter
ValueCountFrequency (%)
S37
59.7%
D7
 
11.3%
A7
 
11.3%
T5
 
8.1%
R3
 
4.8%
N2
 
3.2%
G1
 
1.6%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin455
98.7%
Common6
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t48
10.5%
i43
 
9.5%
e39
 
8.6%
r38
 
8.4%
S37
 
8.1%
c33
 
7.3%
p31
 
6.8%
d26
 
5.7%
o25
 
5.5%
a23
 
5.1%
Other values (15)112
24.6%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t48
10.4%
i43
 
9.3%
e39
 
8.5%
r38
 
8.2%
S37
 
8.0%
c33
 
7.2%
p31
 
6.7%
d26
 
5.6%
o25
 
5.4%
a23
 
5.0%
Other values (16)118
25.6%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct16
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size576.0 B
English
14 
Dutch
Swedish
Norwegian
Russian
Other values (11)
19 

Length

Max length10
Median length7
Mean length7.053571429
Min length5

Characters and Unicode

Total characters395
Distinct characters32
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)12.5%

Sample

1st rowRussian
2nd rowChinese
3rd rowChinese
4th rowChinese
5th rowJapanese

Common Values

ValueCountFrequency (%)
English14
25.0%
Dutch8
14.3%
Swedish6
10.7%
Norwegian5
 
8.9%
Russian4
 
7.1%
Chinese4
 
7.1%
Japanese4
 
7.1%
Spanish2
 
3.6%
Arabic2
 
3.6%
Korean1
 
1.8%
Other values (6)6
10.7%

Length

2022-09-05T21:38:31.656084image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english14
25.0%
dutch8
14.3%
swedish6
10.7%
norwegian5
 
8.9%
russian4
 
7.1%
chinese4
 
7.1%
japanese4
 
7.1%
spanish2
 
3.6%
arabic2
 
3.6%
korean1
 
1.8%
Other values (6)6
10.7%

Most occurring characters

ValueCountFrequency (%)
i43
 
10.9%
n41
 
10.4%
s40
 
10.1%
h36
 
9.1%
a31
 
7.8%
e30
 
7.6%
g22
 
5.6%
l15
 
3.8%
u15
 
3.8%
E14
 
3.5%
Other values (22)108
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter339
85.8%
Uppercase Letter56
 
14.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i43
12.7%
n41
12.1%
s40
11.8%
h36
10.6%
a31
9.1%
e30
8.8%
g22
 
6.5%
l15
 
4.4%
u15
 
4.4%
w11
 
3.2%
Other values (9)55
16.2%
Uppercase Letter
ValueCountFrequency (%)
E14
25.0%
D9
16.1%
S8
14.3%
N5
 
8.9%
R5
 
8.9%
C4
 
7.1%
J4
 
7.1%
A2
 
3.6%
K1
 
1.8%
U1
 
1.8%
Other values (3)3
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
Latin395
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i43
 
10.9%
n41
 
10.4%
s40
 
10.1%
h36
 
9.1%
a31
 
7.8%
e30
 
7.6%
g22
 
5.6%
l15
 
3.8%
u15
 
3.8%
E14
 
3.5%
Other values (22)108
27.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII395
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i43
 
10.9%
n41
 
10.4%
s40
 
10.1%
h36
 
9.1%
a31
 
7.8%
e30
 
7.6%
g22
 
5.6%
l15
 
3.8%
u15
 
3.8%
E14
 
3.5%
Other values (22)108
27.3%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size576.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size576.0 B
Running
35 
Ended
15 
To Be Determined

Length

Max length16
Median length7
Mean length7.428571429
Min length5

Characters and Unicode

Total characters416
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTo Be Determined
2nd rowRunning
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running35
62.5%
Ended15
26.8%
To Be Determined6
 
10.7%

Length

2022-09-05T21:38:31.746692image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:31.836113image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
running35
51.5%
ended15
22.1%
to6
 
8.8%
be6
 
8.8%
determined6
 
8.8%

Most occurring characters

ValueCountFrequency (%)
n126
30.3%
i41
 
9.9%
e39
 
9.4%
d36
 
8.7%
R35
 
8.4%
u35
 
8.4%
g35
 
8.4%
E15
 
3.6%
12
 
2.9%
T6
 
1.4%
Other values (6)36
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter336
80.8%
Uppercase Letter68
 
16.3%
Space Separator12
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n126
37.5%
i41
 
12.2%
e39
 
11.6%
d36
 
10.7%
u35
 
10.4%
g35
 
10.4%
o6
 
1.8%
t6
 
1.8%
r6
 
1.8%
m6
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
R35
51.5%
E15
22.1%
T6
 
8.8%
B6
 
8.8%
D6
 
8.8%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin404
97.1%
Common12
 
2.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n126
31.2%
i41
 
10.1%
e39
 
9.7%
d36
 
8.9%
R35
 
8.7%
u35
 
8.7%
g35
 
8.7%
E15
 
3.7%
T6
 
1.5%
o6
 
1.5%
Other values (5)30
 
7.4%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n126
30.3%
i41
 
9.9%
e39
 
9.4%
d36
 
8.7%
R35
 
8.4%
u35
 
8.4%
g35
 
8.4%
E15
 
3.6%
12
 
2.9%
T6
 
1.4%
Other values (6)36
 
8.7%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct14
Distinct (%)31.8%
Missing12
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean51.75
Minimum8
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:31.907217image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile12.45
Q124.25
median45
Q352.5
95-th percentile120
Maximum180
Range172
Interquartile range (IQR)28.25

Descriptive statistics

Standard deviation41.47631714
Coefficient of variation (CV)0.8014747274
Kurtosis2.829067899
Mean51.75
Median Absolute Deviation (MAD)15
Skewness1.788911312
Sum2277
Variance1720.284884
MonotonicityNot monotonic
2022-09-05T21:38:31.992492image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4511
19.6%
1205
8.9%
604
 
7.1%
304
 
7.1%
403
 
5.4%
153
 
5.4%
223
 
5.4%
122
 
3.6%
202
 
3.6%
422
 
3.6%
Other values (4)5
8.9%
(Missing)12
21.4%
ValueCountFrequency (%)
81
 
1.8%
122
 
3.6%
153
 
5.4%
202
 
3.6%
223
 
5.4%
251
 
1.8%
304
 
7.1%
403
 
5.4%
422
 
3.6%
4511
19.6%
ValueCountFrequency (%)
1802
 
3.6%
1205
8.9%
604
 
7.1%
501
 
1.8%
4511
19.6%
422
 
3.6%
403
 
5.4%
304
 
7.1%
251
 
1.8%
223
 
5.4%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct30
Distinct (%)57.7%
Missing4
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean46.96153846
Minimum5
Maximum188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:32.082827image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile10.65
Q122
median42
Q355.25
95-th percentile120
Maximum188
Range183
Interquartile range (IQR)33.25

Descriptive statistics

Standard deviation34.97223635
Coefficient of variation (CV)0.7446995455
Kurtosis4.691640848
Mean46.96153846
Median Absolute Deviation (MAD)16
Skewness1.919028428
Sum2442
Variance1223.057315
MonotonicityNot monotonic
2022-09-05T21:38:32.186007image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
488
 
14.3%
1204
 
7.1%
293
 
5.4%
223
 
5.4%
452
 
3.6%
422
 
3.6%
602
 
3.6%
382
 
3.6%
402
 
3.6%
202
 
3.6%
Other values (20)22
39.3%
(Missing)4
 
7.1%
ValueCountFrequency (%)
51
 
1.8%
81
 
1.8%
91
 
1.8%
122
3.6%
152
3.6%
161
 
1.8%
202
3.6%
211
 
1.8%
223
5.4%
251
 
1.8%
ValueCountFrequency (%)
1881
 
1.8%
1204
7.1%
981
 
1.8%
771
 
1.8%
641
 
1.8%
602
3.6%
591
 
1.8%
571
 
1.8%
561
 
1.8%
551
 
1.8%

_embedded.show.premiered
Categorical

HIGH CORRELATION

Distinct39
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Memory size576.0 B
2017-09-10
2020-12-06
2020-11-29
2020-11-22
 
3
2018-07-13
 
2
Other values (34)
34 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters560
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)60.7%

Sample

1st row2020-05-22
2nd row2020-10-18
3rd row2020-11-29
4th row2020-03-08
5th row2013-01-30

Common Values

ValueCountFrequency (%)
2017-09-108
 
14.3%
2020-12-065
 
8.9%
2020-11-294
 
7.1%
2020-11-223
 
5.4%
2018-07-132
 
3.6%
2019-07-291
 
1.8%
2018-10-111
 
1.8%
2020-05-041
 
1.8%
2016-09-111
 
1.8%
2019-12-291
 
1.8%
Other values (29)29
51.8%

Length

2022-09-05T21:38:32.274606image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-09-108
 
14.3%
2020-12-065
 
8.9%
2020-11-294
 
7.1%
2020-11-223
 
5.4%
2018-07-132
 
3.6%
2020-10-131
 
1.8%
2020-03-081
 
1.8%
2013-01-301
 
1.8%
2019-07-211
 
1.8%
2020-10-251
 
1.8%
Other values (29)29
51.8%

Most occurring characters

ValueCountFrequency (%)
0149
26.6%
2118
21.1%
-112
20.0%
198
17.5%
923
 
4.1%
716
 
2.9%
612
 
2.1%
810
 
1.8%
39
 
1.6%
58
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number448
80.0%
Dash Punctuation112
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0149
33.3%
2118
26.3%
198
21.9%
923
 
5.1%
716
 
3.6%
612
 
2.7%
810
 
2.2%
39
 
2.0%
58
 
1.8%
45
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
-112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common560
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0149
26.6%
2118
21.1%
-112
20.0%
198
17.5%
923
 
4.1%
716
 
2.9%
612
 
2.1%
810
 
1.8%
39
 
1.6%
58
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0149
26.6%
2118
21.1%
-112
20.0%
198
17.5%
923
 
4.1%
716
 
2.9%
612
 
2.1%
810
 
1.8%
39
 
1.6%
58
 
1.4%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)46.7%
Missing41
Missing (%)73.2%
Memory size576.0 B
2020-12-06
2020-12-13
2020-12-24
2020-12-27
2021-03-13
Other values (2)

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters150
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)33.3%

Sample

1st row2020-12-13
2nd row2020-12-24
3rd row2020-12-27
4th row2020-12-06
5th row2020-12-06

Common Values

ValueCountFrequency (%)
2020-12-068
 
14.3%
2020-12-132
 
3.6%
2020-12-241
 
1.8%
2020-12-271
 
1.8%
2021-03-131
 
1.8%
2021-01-311
 
1.8%
2021-11-281
 
1.8%
(Missing)41
73.2%

Length

2022-09-05T21:38:32.357430image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:32.462749image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-068
53.3%
2020-12-132
 
13.3%
2020-12-241
 
6.7%
2020-12-271
 
6.7%
2021-03-131
 
6.7%
2021-01-311
 
6.7%
2021-11-281
 
6.7%

Most occurring characters

ValueCountFrequency (%)
245
30.0%
037
24.7%
-30
20.0%
122
14.7%
68
 
5.3%
35
 
3.3%
41
 
0.7%
71
 
0.7%
81
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number120
80.0%
Dash Punctuation30
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
245
37.5%
037
30.8%
122
18.3%
68
 
6.7%
35
 
4.2%
41
 
0.8%
71
 
0.8%
81
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
-30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
245
30.0%
037
24.7%
-30
20.0%
122
14.7%
68
 
5.3%
35
 
3.3%
41
 
0.7%
71
 
0.7%
81
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
245
30.0%
037
24.7%
-30
20.0%
122
14.7%
68
 
5.3%
35
 
3.3%
41
 
0.7%
71
 
0.7%
81
 
0.7%

_embedded.show.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct44
Distinct (%)80.0%
Missing1
Missing (%)1.8%
Memory size576.0 B
https://www.videoland.com/series/1062/meisje-van-plezier/1976
https://www.discoveryplus.se/program/pappas-pojkar
 
3
https://disneynow.com/shows/fancy-nancy
 
2
https://www.cmore.se/serie/208411-lassemajas-detektivbyra
 
2
https://premier.one/show/12420
 
1
Other values (39)
39 

Length

Max length85
Median length61
Mean length49.47272727
Min length21

Characters and Unicode

Total characters2721
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)72.7%

Sample

1st rowhttps://premier.one/show/12420
2nd rowhttps://v.qq.com/detail/q/q72jd29a3oxflsr.html
3rd rowhttps://v.qq.com/detail/3/324olz7ilvo2j5f.html
4th rowhttps://v.qq.com/detail/m/7q544xyrava3vxf.html
5th rowhttps://www.ddtpro.com/

Common Values

ValueCountFrequency (%)
https://www.videoland.com/series/1062/meisje-van-plezier/19768
 
14.3%
https://www.discoveryplus.se/program/pappas-pojkar3
 
5.4%
https://disneynow.com/shows/fancy-nancy2
 
3.6%
https://www.cmore.se/serie/208411-lassemajas-detektivbyra2
 
3.6%
https://premier.one/show/124201
 
1.8%
https://motherlandsrpg.com1
 
1.8%
https://www.patrickcotnoir.com/glts1
 
1.8%
http://www.laisves.tv1
 
1.8%
https://shahid.mbc.net/en/series/Al-Anisa-Farah/series-3936341
 
1.8%
https://www.amazon.co.uk/Ghost-Dimension-Lock-Down/dp/B08NVYQ73R1
 
1.8%
Other values (34)34
60.7%

Length

2022-09-05T21:38:32.579831image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.videoland.com/series/1062/meisje-van-plezier/19768
 
14.5%
https://www.discoveryplus.se/program/pappas-pojkar3
 
5.5%
https://disneynow.com/shows/fancy-nancy2
 
3.6%
https://www.cmore.se/serie/208411-lassemajas-detektivbyra2
 
3.6%
http://www.njpw1972.com1
 
1.8%
https://es.hboespana.com/series/30-coins/37b0ccfe-0bf1-489e-b2a3-cae9f6307eb61
 
1.8%
https://v.qq.com/detail/3/324olz7ilvo2j5f.html1
 
1.8%
https://v.qq.com/detail/m/7q544xyrava3vxf.html1
 
1.8%
https://www.ddtpro.com1
 
1.8%
https://www.bilibili.com/bangumi/media/md43146221
 
1.8%
Other values (34)34
61.8%

Most occurring characters

ValueCountFrequency (%)
/248
 
9.1%
e199
 
7.3%
t182
 
6.7%
s173
 
6.4%
o128
 
4.7%
a118
 
4.3%
i115
 
4.2%
w114
 
4.2%
p108
 
4.0%
.104
 
3.8%
Other values (58)1232
45.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1951
71.7%
Other Punctuation410
 
15.1%
Decimal Number204
 
7.5%
Dash Punctuation77
 
2.8%
Uppercase Letter75
 
2.8%
Math Symbol2
 
0.1%
Connector Punctuation2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e199
 
10.2%
t182
 
9.3%
s173
 
8.9%
o128
 
6.6%
a118
 
6.0%
i115
 
5.9%
w114
 
5.8%
p108
 
5.5%
n96
 
4.9%
r95
 
4.9%
Other values (16)623
31.9%
Uppercase Letter
ValueCountFrequency (%)
L6
 
8.0%
C6
 
8.0%
B6
 
8.0%
H5
 
6.7%
F5
 
6.7%
A5
 
6.7%
T5
 
6.7%
D4
 
5.3%
Y4
 
5.3%
W3
 
4.0%
Other values (14)26
34.7%
Decimal Number
ValueCountFrequency (%)
133
16.2%
230
14.7%
626
12.7%
722
10.8%
022
10.8%
419
9.3%
318
8.8%
917
8.3%
59
 
4.4%
88
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/248
60.5%
.104
25.4%
:55
 
13.4%
?2
 
0.5%
%1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
-77
100.0%
Math Symbol
ValueCountFrequency (%)
=2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2026
74.5%
Common695
 
25.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e199
 
9.8%
t182
 
9.0%
s173
 
8.5%
o128
 
6.3%
a118
 
5.8%
i115
 
5.7%
w114
 
5.6%
p108
 
5.3%
n96
 
4.7%
r95
 
4.7%
Other values (40)698
34.5%
Common
ValueCountFrequency (%)
/248
35.7%
.104
15.0%
-77
 
11.1%
:55
 
7.9%
133
 
4.7%
230
 
4.3%
626
 
3.7%
722
 
3.2%
022
 
3.2%
419
 
2.7%
Other values (8)59
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2721
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/248
 
9.1%
e199
 
7.3%
t182
 
6.7%
s173
 
6.4%
o128
 
4.7%
a118
 
4.3%
i115
 
4.2%
w114
 
4.2%
p108
 
4.0%
.104
 
3.8%
Other values (58)1232
45.3%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size576.0 B
41 
10:00
 
3
12:00
 
3
06:00
 
2
20:00
 
2
Other values (5)

Length

Max length5
Median length0
Mean length1.339285714
Min length0

Characters and Unicode

Total characters75
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)8.9%

Sample

1st row
2nd row10:00
3rd row10:00
4th row10:00
5th row12:00

Common Values

ValueCountFrequency (%)
41
73.2%
10:003
 
5.4%
12:003
 
5.4%
06:002
 
3.6%
20:002
 
3.6%
17:001
 
1.8%
21:001
 
1.8%
14:001
 
1.8%
22:301
 
1.8%
22:151
 
1.8%

Length

2022-09-05T21:38:32.682649image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:32.782630image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
10:003
20.0%
12:003
20.0%
06:002
13.3%
20:002
13.3%
17:001
 
6.7%
21:001
 
6.7%
14:001
 
6.7%
22:301
 
6.7%
22:151
 
6.7%

Most occurring characters

ValueCountFrequency (%)
034
45.3%
:15
20.0%
110
 
13.3%
210
 
13.3%
62
 
2.7%
71
 
1.3%
41
 
1.3%
31
 
1.3%
51
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number60
80.0%
Other Punctuation15
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
034
56.7%
110
 
16.7%
210
 
16.7%
62
 
3.3%
71
 
1.7%
41
 
1.7%
31
 
1.7%
51
 
1.7%
Other Punctuation
ValueCountFrequency (%)
:15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common75
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
034
45.3%
:15
20.0%
110
 
13.3%
210
 
13.3%
62
 
2.7%
71
 
1.3%
41
 
1.3%
31
 
1.3%
51
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII75
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
034
45.3%
:15
20.0%
110
 
13.3%
210
 
13.3%
62
 
2.7%
71
 
1.3%
41
 
1.3%
31
 
1.3%
51
 
1.3%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size576.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing51
Missing (%)91.1%
Memory size576.0 B
7.7
8.0
8.1
8.2
7.2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters15
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row7.7
2nd row8.0
3rd row8.1
4th row8.2
5th row7.2

Common Values

ValueCountFrequency (%)
7.71
 
1.8%
8.01
 
1.8%
8.11
 
1.8%
8.21
 
1.8%
7.21
 
1.8%
(Missing)51
91.1%

Length

2022-09-05T21:38:32.864875image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:32.951830image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.71
20.0%
8.01
20.0%
8.11
20.0%
8.21
20.0%
7.21
20.0%

Most occurring characters

ValueCountFrequency (%)
.5
33.3%
73
20.0%
83
20.0%
22
 
13.3%
01
 
6.7%
11
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number10
66.7%
Other Punctuation5
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
73
30.0%
83
30.0%
22
20.0%
01
 
10.0%
11
 
10.0%
Other Punctuation
ValueCountFrequency (%)
.5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.5
33.3%
73
20.0%
83
20.0%
22
 
13.3%
01
 
6.7%
11
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.5
33.3%
73
20.0%
83
20.0%
22
 
13.3%
01
 
6.7%
11
 
6.7%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct37
Distinct (%)66.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.83928571
Minimum2
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:33.043842image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q120.75
median37.5
Q359
95-th percentile85.75
Maximum93
Range91
Interquartile range (IQR)38.25

Descriptive statistics

Standard deviation25.71082318
Coefficient of variation (CV)0.614513913
Kurtosis-0.8941730491
Mean41.83928571
Median Absolute Deviation (MAD)21.5
Skewness0.3044813813
Sum2343
Variance661.0464286
MonotonicityNot monotonic
2022-09-05T21:38:33.146792image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
598
 
14.3%
273
 
5.4%
33
 
5.4%
203
 
5.4%
352
 
3.6%
222
 
3.6%
602
 
3.6%
822
 
3.6%
362
 
3.6%
152
 
3.6%
Other values (27)27
48.2%
ValueCountFrequency (%)
21
 
1.8%
33
5.4%
41
 
1.8%
81
 
1.8%
141
 
1.8%
152
3.6%
161
 
1.8%
191
 
1.8%
203
5.4%
211
 
1.8%
ValueCountFrequency (%)
931
1.8%
921
1.8%
881
1.8%
851
1.8%
822
3.6%
801
1.8%
781
1.8%
721
1.8%
681
1.8%
602
3.6%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct28
Distinct (%)51.9%
Missing2
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean140.7592593
Minimum3
Maximum443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:33.247130image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile12
Q121
median104
Q3238
95-th percentile379
Maximum443
Range440
Interquartile range (IQR)217

Descriptive statistics

Standard deviation133.9574609
Coefficient of variation (CV)0.9516777908
Kurtosis-0.8621575499
Mean140.7592593
Median Absolute Deviation (MAD)87.5
Skewness0.6912407442
Sum7601
Variance17944.60133
MonotonicityNot monotonic
2022-09-05T21:38:33.346226image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
219
16.1%
128
14.3%
1733
 
5.4%
1043
 
5.4%
2383
 
5.4%
1702
 
3.6%
3792
 
3.6%
3272
 
3.6%
152
 
3.6%
832
 
3.6%
Other values (18)18
32.1%
(Missing)2
 
3.6%
ValueCountFrequency (%)
31
 
1.8%
128
14.3%
152
 
3.6%
219
16.1%
221
 
1.8%
321
 
1.8%
511
 
1.8%
832
 
3.6%
1031
 
1.8%
1043
 
5.4%
ValueCountFrequency (%)
4431
1.8%
4081
1.8%
3792
3.6%
3771
1.8%
3311
1.8%
3272
3.6%
3211
1.8%
3041
1.8%
2941
1.8%
2811
1.8%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct28
Distinct (%)51.9%
Missing2
Missing (%)3.6%
Memory size576.0 B
YouTube
Videoland
discovery+
Tencent QQ
NRK TV
Other values (23)
28 

Length

Max length19
Median length12
Mean length8.5
Min length4

Characters and Unicode

Total characters459
Distinct characters46
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)33.3%

Sample

1st rowPremier
2nd rowTencent QQ
3rd rowTencent QQ
4th rowTencent QQ
5th rowDDTUniverse

Common Values

ValueCountFrequency (%)
YouTube9
16.1%
Videoland8
14.3%
discovery+3
 
5.4%
Tencent QQ3
 
5.4%
NRK TV3
 
5.4%
C More2
 
3.6%
Shahid2
 
3.6%
TV 2 Play2
 
3.6%
WWE Network2
 
3.6%
DisneyNOW2
 
3.6%
Other values (18)18
32.1%
(Missing)2
 
3.6%

Length

2022-09-05T21:38:33.452578image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube9
 
12.0%
videoland8
 
10.7%
tv6
 
8.0%
play3
 
4.0%
discovery3
 
4.0%
tencent3
 
4.0%
qq3
 
4.0%
nrk3
 
4.0%
disneynow2
 
2.7%
wwe2
 
2.7%
Other values (28)33
44.0%

Most occurring characters

ValueCountFrequency (%)
e44
 
9.6%
o35
 
7.6%
d25
 
5.4%
i25
 
5.4%
a23
 
5.0%
T22
 
4.8%
21
 
4.6%
u21
 
4.6%
l20
 
4.4%
n19
 
4.1%
Other values (36)204
44.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter304
66.2%
Uppercase Letter127
27.7%
Space Separator21
 
4.6%
Math Symbol5
 
1.1%
Decimal Number2
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T22
17.3%
V17
13.4%
P10
 
7.9%
N9
 
7.1%
Y9
 
7.1%
W9
 
7.1%
Q6
 
4.7%
R6
 
4.7%
S6
 
4.7%
E5
 
3.9%
Other values (13)28
22.0%
Lowercase Letter
ValueCountFrequency (%)
e44
14.5%
o35
11.5%
d25
 
8.2%
i25
 
8.2%
a23
 
7.6%
u21
 
6.9%
l20
 
6.6%
n19
 
6.2%
r17
 
5.6%
t12
 
3.9%
Other values (10)63
20.7%
Space Separator
ValueCountFrequency (%)
21
100.0%
Math Symbol
ValueCountFrequency (%)
+5
100.0%
Decimal Number
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin431
93.9%
Common28
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e44
 
10.2%
o35
 
8.1%
d25
 
5.8%
i25
 
5.8%
a23
 
5.3%
T22
 
5.1%
u21
 
4.9%
l20
 
4.6%
n19
 
4.4%
V17
 
3.9%
Other values (33)180
41.8%
Common
ValueCountFrequency (%)
21
75.0%
+5
 
17.9%
22
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e44
 
9.6%
o35
 
7.6%
d25
 
5.4%
i25
 
5.4%
a23
 
5.0%
T22
 
4.8%
21
 
4.6%
u21
 
4.6%
l20
 
4.4%
n19
 
4.1%
Other values (36)204
44.4%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)30.3%
Missing23
Missing (%)41.1%
Memory size576.0 B
Netherlands
United States
Norway
China
Sweden
Other values (5)

Length

Max length18
Median length13
Mean length9.212121212
Min length5

Characters and Unicode

Total characters304
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)12.1%

Sample

1st rowRussian Federation
2nd rowChina
3rd rowChina
4th rowChina
5th rowJapan

Common Values

ValueCountFrequency (%)
Netherlands8
 
14.3%
United States7
 
12.5%
Norway5
 
8.9%
China4
 
7.1%
Sweden3
 
5.4%
Japan2
 
3.6%
Russian Federation1
 
1.8%
Korea, Republic of1
 
1.8%
Spain1
 
1.8%
Brazil1
 
1.8%
(Missing)23
41.1%

Length

2022-09-05T21:38:33.558733image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:33.675211image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
netherlands8
18.6%
united7
16.3%
states7
16.3%
norway5
11.6%
china4
9.3%
sweden3
 
7.0%
japan2
 
4.7%
russian1
 
2.3%
federation1
 
2.3%
korea1
 
2.3%
Other values (4)4
9.3%

Most occurring characters

ValueCountFrequency (%)
e40
13.2%
a33
10.9%
t30
 
9.9%
n27
 
8.9%
d19
 
6.2%
s17
 
5.6%
r16
 
5.3%
i16
 
5.3%
N13
 
4.3%
h12
 
3.9%
Other values (20)81
26.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter251
82.6%
Uppercase Letter42
 
13.8%
Space Separator10
 
3.3%
Other Punctuation1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e40
15.9%
a33
13.1%
t30
12.0%
n27
10.8%
d19
7.6%
s17
6.8%
r16
 
6.4%
i16
 
6.4%
h12
 
4.8%
l10
 
4.0%
Other values (9)31
12.4%
Uppercase Letter
ValueCountFrequency (%)
N13
31.0%
S11
26.2%
U7
16.7%
C4
 
9.5%
J2
 
4.8%
R2
 
4.8%
F1
 
2.4%
K1
 
2.4%
B1
 
2.4%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin293
96.4%
Common11
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e40
13.7%
a33
11.3%
t30
10.2%
n27
 
9.2%
d19
 
6.5%
s17
 
5.8%
r16
 
5.5%
i16
 
5.5%
N13
 
4.4%
h12
 
4.1%
Other values (18)70
23.9%
Common
ValueCountFrequency (%)
10
90.9%
,1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e40
13.2%
a33
10.9%
t30
 
9.9%
n27
 
8.9%
d19
 
6.2%
s17
 
5.6%
r16
 
5.3%
i16
 
5.3%
N13
 
4.3%
h12
 
3.9%
Other values (20)81
26.6%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)30.3%
Missing23
Missing (%)41.1%
Memory size576.0 B
NL
US
NO
CN
SE
Other values (5)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters66
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)12.1%

Sample

1st rowRU
2nd rowCN
3rd rowCN
4th rowCN
5th rowJP

Common Values

ValueCountFrequency (%)
NL8
 
14.3%
US7
 
12.5%
NO5
 
8.9%
CN4
 
7.1%
SE3
 
5.4%
JP2
 
3.6%
RU1
 
1.8%
KR1
 
1.8%
ES1
 
1.8%
BR1
 
1.8%
(Missing)23
41.1%

Length

2022-09-05T21:38:33.769054image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:33.872136image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
nl8
24.2%
us7
21.2%
no5
15.2%
cn4
12.1%
se3
 
9.1%
jp2
 
6.1%
ru1
 
3.0%
kr1
 
3.0%
es1
 
3.0%
br1
 
3.0%

Most occurring characters

ValueCountFrequency (%)
N17
25.8%
S11
16.7%
L8
12.1%
U8
12.1%
O5
 
7.6%
C4
 
6.1%
E4
 
6.1%
R3
 
4.5%
J2
 
3.0%
P2
 
3.0%
Other values (2)2
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter66
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N17
25.8%
S11
16.7%
L8
12.1%
U8
12.1%
O5
 
7.6%
C4
 
6.1%
E4
 
6.1%
R3
 
4.5%
J2
 
3.0%
P2
 
3.0%
Other values (2)2
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Latin66
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N17
25.8%
S11
16.7%
L8
12.1%
U8
12.1%
O5
 
7.6%
C4
 
6.1%
E4
 
6.1%
R3
 
4.5%
J2
 
3.0%
P2
 
3.0%
Other values (2)2
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N17
25.8%
S11
16.7%
L8
12.1%
U8
12.1%
O5
 
7.6%
C4
 
6.1%
E4
 
6.1%
R3
 
4.5%
J2
 
3.0%
P2
 
3.0%
Other values (2)2
 
3.0%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)30.3%
Missing23
Missing (%)41.1%
Memory size576.0 B
Europe/Amsterdam
America/New_York
Europe/Oslo
Asia/Shanghai
Europe/Stockholm
Other values (5)

Length

Max length16
Median length16
Mean length14.15151515
Min length10

Characters and Unicode

Total characters467
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)12.1%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Shanghai
3rd rowAsia/Shanghai
4th rowAsia/Shanghai
5th rowAsia/Tokyo

Common Values

ValueCountFrequency (%)
Europe/Amsterdam8
 
14.3%
America/New_York7
 
12.5%
Europe/Oslo5
 
8.9%
Asia/Shanghai4
 
7.1%
Europe/Stockholm3
 
5.4%
Asia/Tokyo2
 
3.6%
Asia/Kamchatka1
 
1.8%
Asia/Seoul1
 
1.8%
Europe/Madrid1
 
1.8%
America/Noronha1
 
1.8%
(Missing)23
41.1%

Length

2022-09-05T21:38:33.968781image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:34.083010image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/amsterdam8
24.2%
america/new_york7
21.2%
europe/oslo5
15.2%
asia/shanghai4
12.1%
europe/stockholm3
 
9.1%
asia/tokyo2
 
6.1%
asia/kamchatka1
 
3.0%
asia/seoul1
 
3.0%
europe/madrid1
 
3.0%
america/noronha1
 
3.0%

Most occurring characters

ValueCountFrequency (%)
r42
 
9.0%
o42
 
9.0%
e41
 
8.8%
a37
 
7.9%
/33
 
7.1%
m28
 
6.0%
A24
 
5.1%
s21
 
4.5%
i21
 
4.5%
u18
 
3.9%
Other values (20)160
34.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter354
75.8%
Uppercase Letter73
 
15.6%
Other Punctuation33
 
7.1%
Connector Punctuation7
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r42
11.9%
o42
11.9%
e41
11.6%
a37
10.5%
m28
 
7.9%
s21
 
5.9%
i21
 
5.9%
u18
 
5.1%
p17
 
4.8%
k13
 
3.7%
Other values (9)74
20.9%
Uppercase Letter
ValueCountFrequency (%)
A24
32.9%
E17
23.3%
S8
 
11.0%
N8
 
11.0%
Y7
 
9.6%
O5
 
6.8%
T2
 
2.7%
K1
 
1.4%
M1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/33
100.0%
Connector Punctuation
ValueCountFrequency (%)
_7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin427
91.4%
Common40
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r42
 
9.8%
o42
 
9.8%
e41
 
9.6%
a37
 
8.7%
m28
 
6.6%
A24
 
5.6%
s21
 
4.9%
i21
 
4.9%
u18
 
4.2%
E17
 
4.0%
Other values (18)136
31.9%
Common
ValueCountFrequency (%)
/33
82.5%
_7
 
17.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII467
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r42
 
9.0%
o42
 
9.0%
e41
 
8.8%
a37
 
7.9%
/33
 
7.1%
m28
 
6.0%
A24
 
5.1%
s21
 
4.5%
i21
 
4.5%
u18
 
3.9%
Other values (20)160
34.3%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)29.6%
Missing29
Missing (%)51.8%
Memory size576.0 B
https://www.youtube.com
https://www.videoland.com/
https://v.qq.com/
https://www.discoveryplus.com/
https://tv.kakao.com/top
Other values (3)

Length

Max length30
Median length26
Mean length24.25925926
Min length17

Characters and Unicode

Total characters655
Distinct characters24
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)14.8%

Sample

1st rowhttps://v.qq.com/
2nd rowhttps://v.qq.com/
3rd rowhttps://v.qq.com/
4th rowhttps://tv.kakao.com/top
5th rowhttps://www.videoland.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com9
 
16.1%
https://www.videoland.com/8
 
14.3%
https://v.qq.com/3
 
5.4%
https://www.discoveryplus.com/3
 
5.4%
https://tv.kakao.com/top1
 
1.8%
https://viaplay.com1
 
1.8%
https://www.primevideo.com1
 
1.8%
https://www.paramountplus.com/1
 
1.8%
(Missing)29
51.8%

Length

2022-09-05T21:38:34.188804image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:34.296031image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.youtube.com9
33.3%
https://www.videoland.com8
29.6%
https://v.qq.com3
 
11.1%
https://www.discoveryplus.com3
 
11.1%
https://tv.kakao.com/top1
 
3.7%
https://viaplay.com1
 
3.7%
https://www.primevideo.com1
 
3.7%
https://www.paramountplus.com1
 
3.7%

Most occurring characters

ValueCountFrequency (%)
/70
 
10.7%
t66
 
10.1%
w66
 
10.1%
.53
 
8.1%
o51
 
7.8%
p35
 
5.3%
s34
 
5.2%
c30
 
4.6%
m29
 
4.4%
h27
 
4.1%
Other values (14)194
29.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter505
77.1%
Other Punctuation150
 
22.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t66
13.1%
w66
13.1%
o51
10.1%
p35
 
6.9%
s34
 
6.7%
c30
 
5.9%
m29
 
5.7%
h27
 
5.3%
u23
 
4.6%
e22
 
4.4%
Other values (11)122
24.2%
Other Punctuation
ValueCountFrequency (%)
/70
46.7%
.53
35.3%
:27
 
18.0%

Most occurring scripts

ValueCountFrequency (%)
Latin505
77.1%
Common150
 
22.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t66
13.1%
w66
13.1%
o51
10.1%
p35
 
6.9%
s34
 
6.7%
c30
 
5.9%
m29
 
5.7%
h27
 
5.3%
u23
 
4.6%
e22
 
4.4%
Other values (11)122
24.2%
Common
ValueCountFrequency (%)
/70
46.7%
.53
35.3%
:27
 
18.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII655
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/70
 
10.7%
t66
 
10.1%
w66
 
10.1%
.53
 
8.1%
o51
 
7.8%
p35
 
5.3%
s34
 
5.2%
c30
 
4.6%
m29
 
4.4%
h27
 
4.1%
Other values (14)194
29.6%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show.externals.tvrage
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing55
Missing (%)98.2%
Memory size576.0 B
25100.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row25100.0

Common Values

ValueCountFrequency (%)
25100.01
 
1.8%
(Missing)55
98.2%

Length

2022-09-05T21:38:34.395728image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:34.480963image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
25100.01
100.0%

Most occurring characters

ValueCountFrequency (%)
03
42.9%
21
 
14.3%
51
 
14.3%
11
 
14.3%
.1
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
85.7%
Other Punctuation1
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
03
50.0%
21
 
16.7%
51
 
16.7%
11
 
16.7%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
03
42.9%
21
 
14.3%
51
 
14.3%
11
 
14.3%
.1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
03
42.9%
21
 
14.3%
51
 
14.3%
11
 
14.3%
.1
 
14.3%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct30
Distinct (%)73.2%
Missing15
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean353776.7317
Minimum144541
Maximum397721
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:34.560691image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum144541
5-th percentile277691
Q1333829
median366083
Q3390471
95-th percentile392649
Maximum397721
Range253180
Interquartile range (IQR)56642

Descriptive statistics

Standard deviation47363.96722
Coefficient of variation (CV)0.1338809565
Kurtosis8.662195799
Mean353776.7317
Median Absolute Deviation (MAD)25893
Skewness-2.442871531
Sum14504846
Variance2243345391
MonotonicityNot monotonic
2022-09-05T21:38:34.666842image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3338298
 
14.3%
3919763
 
5.4%
3488202
 
3.6%
3911592
 
3.6%
1445411
 
1.8%
3628631
 
1.8%
3373361
 
1.8%
3103361
 
1.8%
2914891
 
1.8%
3936971
 
1.8%
Other values (20)20
35.7%
(Missing)15
26.8%
ValueCountFrequency (%)
1445411
 
1.8%
2651931
 
1.8%
2776911
 
1.8%
2914891
 
1.8%
3103361
 
1.8%
3338298
14.3%
3373361
 
1.8%
3386311
 
1.8%
3488202
 
3.6%
3544581
 
1.8%
ValueCountFrequency (%)
3977211
 
1.8%
3936971
 
1.8%
3926491
 
1.8%
3925981
 
1.8%
3919763
5.4%
3911592
3.6%
3905861
 
1.8%
3904711
 
1.8%
3901301
 
1.8%
3861111
 
1.8%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct24
Distinct (%)68.6%
Missing21
Missing (%)37.5%
Memory size576.0 B
tt7277876
tt13010912
tt13614746
tt2229129
tt11492320
 
1
Other values (19)
19 

Length

Max length10
Median length10
Mean length9.514285714
Min length9

Characters and Unicode

Total characters333
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)57.1%

Sample

1st rowtt10784214
2nd rowtt9348700
3rd rowtt11492320
4th rowtt7277876
5th rowtt7277876

Common Values

ValueCountFrequency (%)
tt72778768
 
14.3%
tt130109123
 
5.4%
tt136147462
 
3.6%
tt22291292
 
3.6%
tt114923201
 
1.8%
tt124856361
 
1.8%
tt16011411
 
1.8%
tt102418121
 
1.8%
tt64686941
 
1.8%
tt03817531
 
1.8%
Other values (14)14
25.0%
(Missing)21
37.5%

Length

2022-09-05T21:38:34.758285image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt72778768
22.9%
tt130109123
 
8.6%
tt136147462
 
5.7%
tt22291292
 
5.7%
tt93487001
 
2.9%
tt97643861
 
2.9%
tt126931481
 
2.9%
tt76948741
 
2.9%
tt107010381
 
2.9%
tt129009661
 
2.9%
Other values (14)14
40.0%

Most occurring characters

ValueCountFrequency (%)
t70
21.0%
743
12.9%
142
12.6%
232
9.6%
632
9.6%
024
 
7.2%
423
 
6.9%
322
 
6.6%
821
 
6.3%
921
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number263
79.0%
Lowercase Letter70
 
21.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
743
16.3%
142
16.0%
232
12.2%
632
12.2%
024
9.1%
423
8.7%
322
8.4%
821
8.0%
921
8.0%
53
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
t70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common263
79.0%
Latin70
 
21.0%

Most frequent character per script

Common
ValueCountFrequency (%)
743
16.3%
142
16.0%
232
12.2%
632
12.2%
024
9.1%
423
8.7%
322
8.4%
821
8.0%
921
8.0%
53
 
1.1%
Latin
ValueCountFrequency (%)
t70
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII333
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t70
21.0%
743
12.9%
142
12.6%
232
9.6%
632
9.6%
024
 
7.2%
423
 
6.9%
322
 
6.6%
821
 
6.3%
921
 
6.3%

_embedded.show.image.medium
Categorical

HIGH CORRELATION
MISSING

Distinct41
Distinct (%)78.8%
Missing4
Missing (%)7.1%
Memory size576.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/234/586607.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/287/718562.jpg
 
3
https://static.tvmaze.com/uploads/images/medium_portrait/161/402691.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/290/725748.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/394/985939.jpg
 
1
Other values (36)
36 

Length

Max length72
Median length71
Mean length71.03846154
Min length70

Characters and Unicode

Total characters3694
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)71.2%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/394/985939.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/279/698895.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/286/715165.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/268/670796.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/234/586607.jpg8
 
14.3%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718562.jpg3
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/161/402691.jpg2
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/290/725748.jpg2
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/394/985939.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729040.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/408/1021576.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/295/739175.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/298/746697.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/308/771760.jpg1
 
1.8%
Other values (31)31
55.4%
(Missing)4
 
7.1%

Length

2022-09-05T21:38:34.846943image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/234/586607.jpg8
 
15.4%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718562.jpg3
 
5.8%
https://static.tvmaze.com/uploads/images/medium_portrait/161/402691.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/medium_portrait/290/725748.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713990.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/286/715165.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/268/670796.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/273/683332.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/217/542797.jpg1
 
1.9%
Other values (31)31
59.6%

Most occurring characters

ValueCountFrequency (%)
t364
 
9.9%
/364
 
9.9%
a260
 
7.0%
m260
 
7.0%
p208
 
5.6%
s208
 
5.6%
i208
 
5.6%
.156
 
4.2%
e156
 
4.2%
o156
 
4.2%
Other values (22)1354
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2600
70.4%
Other Punctuation572
 
15.5%
Decimal Number470
 
12.7%
Connector Punctuation52
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t364
14.0%
a260
10.0%
m260
10.0%
p208
 
8.0%
s208
 
8.0%
i208
 
8.0%
e156
 
6.0%
o156
 
6.0%
g104
 
4.0%
c104
 
4.0%
Other values (8)572
22.0%
Decimal Number
ValueCountFrequency (%)
263
13.4%
760
12.8%
653
11.3%
851
10.9%
149
10.4%
942
8.9%
041
8.7%
440
8.5%
540
8.5%
331
6.6%
Other Punctuation
ValueCountFrequency (%)
/364
63.6%
.156
27.3%
:52
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2600
70.4%
Common1094
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t364
14.0%
a260
10.0%
m260
10.0%
p208
 
8.0%
s208
 
8.0%
i208
 
8.0%
e156
 
6.0%
o156
 
6.0%
g104
 
4.0%
c104
 
4.0%
Other values (8)572
22.0%
Common
ValueCountFrequency (%)
/364
33.3%
.156
14.3%
263
 
5.8%
760
 
5.5%
653
 
4.8%
_52
 
4.8%
:52
 
4.8%
851
 
4.7%
149
 
4.5%
942
 
3.8%
Other values (4)152
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3694
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t364
 
9.9%
/364
 
9.9%
a260
 
7.0%
m260
 
7.0%
p208
 
5.6%
s208
 
5.6%
i208
 
5.6%
.156
 
4.2%
e156
 
4.2%
o156
 
4.2%
Other values (22)1354
36.7%

_embedded.show.image.original
Categorical

HIGH CORRELATION
MISSING

Distinct41
Distinct (%)78.8%
Missing4
Missing (%)7.1%
Memory size576.0 B
https://static.tvmaze.com/uploads/images/original_untouched/234/586607.jpg
https://static.tvmaze.com/uploads/images/original_untouched/287/718562.jpg
 
3
https://static.tvmaze.com/uploads/images/original_untouched/161/402691.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/290/725748.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/394/985939.jpg
 
1
Other values (36)
36 

Length

Max length75
Median length74
Mean length74.03846154
Min length73

Characters and Unicode

Total characters3850
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)71.2%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/394/985939.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/279/698895.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/286/715165.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/268/670796.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/234/586607.jpg8
 
14.3%
https://static.tvmaze.com/uploads/images/original_untouched/287/718562.jpg3
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/161/402691.jpg2
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/290/725748.jpg2
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/394/985939.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/291/729040.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/408/1021576.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/295/739175.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/298/746697.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/308/771760.jpg1
 
1.8%
Other values (31)31
55.4%
(Missing)4
 
7.1%

Length

2022-09-05T21:38:34.943028image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/234/586607.jpg8
 
15.4%
https://static.tvmaze.com/uploads/images/original_untouched/287/718562.jpg3
 
5.8%
https://static.tvmaze.com/uploads/images/original_untouched/161/402691.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/290/725748.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/713990.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/286/715165.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/268/670796.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/273/683332.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/217/542797.jpg1
 
1.9%
Other values (31)31
59.6%

Most occurring characters

ValueCountFrequency (%)
/364
 
9.5%
t312
 
8.1%
a260
 
6.8%
s208
 
5.4%
i208
 
5.4%
o208
 
5.4%
p156
 
4.1%
c156
 
4.1%
.156
 
4.1%
g156
 
4.1%
Other values (23)1666
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2756
71.6%
Other Punctuation572
 
14.9%
Decimal Number470
 
12.2%
Connector Punctuation52
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t312
 
11.3%
a260
 
9.4%
s208
 
7.5%
i208
 
7.5%
o208
 
7.5%
p156
 
5.7%
c156
 
5.7%
g156
 
5.7%
m156
 
5.7%
e156
 
5.7%
Other values (9)780
28.3%
Decimal Number
ValueCountFrequency (%)
263
13.4%
760
12.8%
653
11.3%
851
10.9%
149
10.4%
942
8.9%
041
8.7%
440
8.5%
540
8.5%
331
6.6%
Other Punctuation
ValueCountFrequency (%)
/364
63.6%
.156
27.3%
:52
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2756
71.6%
Common1094
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t312
 
11.3%
a260
 
9.4%
s208
 
7.5%
i208
 
7.5%
o208
 
7.5%
p156
 
5.7%
c156
 
5.7%
g156
 
5.7%
m156
 
5.7%
e156
 
5.7%
Other values (9)780
28.3%
Common
ValueCountFrequency (%)
/364
33.3%
.156
14.3%
263
 
5.8%
760
 
5.5%
653
 
4.8%
:52
 
4.8%
_52
 
4.8%
851
 
4.7%
149
 
4.5%
942
 
3.8%
Other values (4)152
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/364
 
9.5%
t312
 
8.1%
a260
 
6.8%
s208
 
5.4%
i208
 
5.4%
o208
 
5.4%
p156
 
4.1%
c156
 
4.1%
.156
 
4.1%
g156
 
4.1%
Other values (23)1666
43.3%

_embedded.show.summary
Categorical

HIGH CORRELATION
MISSING

Distinct39
Distinct (%)78.0%
Missing6
Missing (%)10.7%
Memory size576.0 B
<p>The marriage of Nadine and Remco seems to be ok: he is making earnings, she is taking care of their kids. Everything seems to be fine, until Remco confesses his cheating on her with her halfsister and leaves. Nadine is inconsolable. But behind her tears, a small fire is spreading. She wants to fight for her self-esteem and radically changes her life.</p>
<p>Once they were the coolest guys in school. Ten years later, they are still partying as if they were carefree teenagers. Now it's high time for daddy's boys to grow up.</p>
 
3
<p><b>Fancy Nancy</b> centers around six-year-old Nancy, a girl who likes to be fancy in everything from her advanced vocabulary to her creative, elaborate attire. Excited to experience what the magnificent world has to offer, Nancy uses her ingenuity and imagination as she learns that while life doesn't always go as planned, it's important to celebrate the differences that make everyone unique.</p>
 
2
<p>This family series revolves around the two friends Lasse and Maja who run a detective agency together in the small town of Valleby. They investigate all possible mysteries and contribute crucial pieces to the police chief, played by Anders Jansson.</p>
 
2
<p><b>AwesomenessTV's Next Influencer</b> follows a group of content creators competing in a series of challenges to prove they have what it takes to become the next big influencer.</p>
 
1
Other values (34)
34 

Length

Max length851
Median length418
Mean length371.4
Min length105

Characters and Unicode

Total characters18570
Distinct characters102
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)70.0%

Sample

1st row<p>The non-fiction series "Maniacs" tells about the most high-profile Russian crimes, in which still not all the circumstances are clear to the end</p>
2nd row<p>Zero was mankind's first real superhero. Under his watch, countless other superheros appeared and followed in his footsteps. However, after 5 years of war, Zero disappeared without a trace.<br /><br />(Source: zeroscans)</p>
3rd row<p>One day, an unexplained RR virus appeared on the earth, drawing the world into disaster. Infected animals mutated into terrible monsters, invaded massively, and humans built walls around the destruction and established the base city as the last bastion for humans. The suffering that mankind has experienced during this period of time is known as the "Great Nirvana Period." Not only that, Luo Feng not only carried the burden of supporting the family but also to protect the human homeland, for the better survival and development of mankind, together with other justice warriors, to join hands against the fierce monsters. Under the desperate situation of the end, can Luo Feng and other warriors repel monsters and successfully protect the human world?</p>
4th row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>
5th row<p>In the twenty-first century, gods and demons can no longer maintain balance due to the rapid development of human society. In an effort to restore proper order, the gods began to take care of saving the world, for which they sent a group of gods and monsters to the world of people, who must find there the " key " to salvation. Su moting is a girl with the personality of "demon child". When her parents asked her to leave home so that she could become independent and independent, she met the beautiful and charming God of Tianjin and the mysterious demon cat. So begins a new turbulent round of su moting's life.</p><p><br /> </p>

Common Values

ValueCountFrequency (%)
<p>The marriage of Nadine and Remco seems to be ok: he is making earnings, she is taking care of their kids. Everything seems to be fine, until Remco confesses his cheating on her with her halfsister and leaves. Nadine is inconsolable. But behind her tears, a small fire is spreading. She wants to fight for her self-esteem and radically changes her life.</p>8
 
14.3%
<p>Once they were the coolest guys in school. Ten years later, they are still partying as if they were carefree teenagers. Now it's high time for daddy's boys to grow up.</p>3
 
5.4%
<p><b>Fancy Nancy</b> centers around six-year-old Nancy, a girl who likes to be fancy in everything from her advanced vocabulary to her creative, elaborate attire. Excited to experience what the magnificent world has to offer, Nancy uses her ingenuity and imagination as she learns that while life doesn't always go as planned, it's important to celebrate the differences that make everyone unique.</p>2
 
3.6%
<p>This family series revolves around the two friends Lasse and Maja who run a detective agency together in the small town of Valleby. They investigate all possible mysteries and contribute crucial pieces to the police chief, played by Anders Jansson.</p>2
 
3.6%
<p><b>AwesomenessTV's Next Influencer</b> follows a group of content creators competing in a series of challenges to prove they have what it takes to become the next big influencer.</p>1
 
1.8%
<p><b>The George Lucas Talk Show</b>, a long-running cult talk show hosted by Connor Ratliff, as George Lucas, his sidekick Watto (Griffin Newman), and his producer Patrick Cotnoir. They interview guests in a panel format weekly on PlanetScum.</p>1
 
1.8%
<p>A show of intellectual satire. The show discusses national and foreign issues in a witty and biting way, and once a month - a topic prepared in detail by the screenwriters. Since the beginning of the fifth season, three hosts have shared the main wheel: Andrius Tapinas, Ignas Grinevičius, and Irma Bogdanovičiūtė.</p>1
 
1.8%
<p>Farah and Shadi are left to deal with the consequences of their son's kidnapping. Between war and peace, Majed and Dalal rediscover their relationship.</p>1
 
1.8%
<p><b>Ghost Dimension Lock Down</b> paranormal investigators take on the UK's most haunting buildings, searching for paranormal activity.  While the world is on lockdown, it appears that the ghosts are not. </p>1
 
1.8%
<p>Our crew is recruited by T.O.R.C.H for what seems like a simple mission of delivering water to a far off planet. They get way more than they bargained for along the way, and maybe learn more about themselves during their adventures. Storyteller Eugenio Vargas leads cast members Krystina Arielle, DeejayKnight, Tanya DePass and Michael Sinclair II on a 12 session run around their galaxy and their home planet.</p>1
 
1.8%
Other values (29)29
51.8%
(Missing)6
 
10.7%

Length

2022-09-05T21:38:35.063730image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the172
 
5.7%
and116
 
3.8%
to95
 
3.1%
of89
 
2.9%
a63
 
2.1%
is60
 
2.0%
her56
 
1.8%
in55
 
1.8%
with29
 
1.0%
they26
 
0.9%
Other values (1168)2281
75.0%

Most occurring characters

ValueCountFrequency (%)
2987
16.1%
e1839
 
9.9%
a1169
 
6.3%
t1154
 
6.2%
n1049
 
5.6%
i1042
 
5.6%
s1024
 
5.5%
o993
 
5.3%
r911
 
4.9%
h761
 
4.1%
Other values (92)5641
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14115
76.0%
Space Separator2994
 
16.1%
Uppercase Letter548
 
3.0%
Other Punctuation495
 
2.7%
Math Symbol316
 
1.7%
Dash Punctuation40
 
0.2%
Decimal Number34
 
0.2%
Open Punctuation8
 
< 0.1%
Close Punctuation8
 
< 0.1%
Other Letter8
 
< 0.1%
Other values (3)4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1839
13.0%
a1169
 
8.3%
t1154
 
8.2%
n1049
 
7.4%
i1042
 
7.4%
s1024
 
7.3%
o993
 
7.0%
r911
 
6.5%
h761
 
5.4%
l556
 
3.9%
Other values (24)3617
25.6%
Uppercase Letter
ValueCountFrequency (%)
T61
 
11.1%
S53
 
9.7%
N47
 
8.6%
W46
 
8.4%
R30
 
5.5%
E27
 
4.9%
H22
 
4.0%
A22
 
4.0%
F21
 
3.8%
G21
 
3.8%
Other values (17)198
36.1%
Other Punctuation
ValueCountFrequency (%)
,165
33.3%
.164
33.1%
/82
16.6%
'35
 
7.1%
"15
 
3.0%
:14
 
2.8%
!12
 
2.4%
?6
 
1.2%
@1
 
0.2%
#1
 
0.2%
Decimal Number
ValueCountFrequency (%)
012
35.3%
27
20.6%
15
14.7%
83
 
8.8%
93
 
8.8%
42
 
5.9%
51
 
2.9%
71
 
2.9%
Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Dash Punctuation
ValueCountFrequency (%)
-30
75.0%
8
 
20.0%
2
 
5.0%
Space Separator
ValueCountFrequency (%)
2987
99.8%
 7
 
0.2%
Math Symbol
ValueCountFrequency (%)
<158
50.0%
>158
50.0%
Open Punctuation
ValueCountFrequency (%)
(7
87.5%
[1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
)7
87.5%
]1
 
12.5%
Currency Symbol
ValueCountFrequency (%)
$1
50.0%
1
50.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin14663
79.0%
Common3899
 
21.0%
Han4
 
< 0.1%
Katakana4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1839
12.5%
a1169
 
8.0%
t1154
 
7.9%
n1049
 
7.2%
i1042
 
7.1%
s1024
 
7.0%
o993
 
6.8%
r911
 
6.2%
h761
 
5.2%
l556
 
3.8%
Other values (51)4165
28.4%
Common
ValueCountFrequency (%)
2987
76.6%
,165
 
4.2%
.164
 
4.2%
<158
 
4.1%
>158
 
4.1%
/82
 
2.1%
'35
 
0.9%
-30
 
0.8%
"15
 
0.4%
:14
 
0.4%
Other values (23)91
 
2.3%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII18526
99.8%
None23
 
0.1%
Punctuation10
 
0.1%
Katakana5
 
< 0.1%
CJK4
 
< 0.1%
Dingbats1
 
< 0.1%
Currency Symbols1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2987
16.1%
e1839
 
9.9%
a1169
 
6.3%
t1154
 
6.2%
n1049
 
5.7%
i1042
 
5.6%
s1024
 
5.5%
o993
 
5.4%
r911
 
4.9%
h761
 
4.1%
Other values (69)5597
30.2%
Punctuation
ValueCountFrequency (%)
8
80.0%
2
 
20.0%
None
ValueCountFrequency (%)
 7
30.4%
ä3
13.0%
Å2
 
8.7%
å2
 
8.7%
é2
 
8.7%
ö2
 
8.7%
č2
 
8.7%
ā1
 
4.3%
ė1
 
4.3%
ū1
 
4.3%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Dingbats
ValueCountFrequency (%)
1
100.0%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct45
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1642434872
Minimum1603467037
Maximum1662206917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:35.187298image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1603467037
5-th percentile1609338596
Q11627866813
median1649498019
Q31654362617
95-th percentile1661573548
Maximum1662206917
Range58739880
Interquartile range (IQR)26495804.25

Descriptive statistics

Standard deviation17931726.62
Coefficient of variation (CV)0.01091777027
Kurtosis-0.775966792
Mean1642434872
Median Absolute Deviation (MAD)11558358
Skewness-0.7920383317
Sum9.197635285 × 1010
Variance3.215468197 × 1014
MonotonicityNot monotonic
2022-09-05T21:38:35.308674image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
16524828118
 
14.3%
16532523563
 
5.4%
16573745032
 
3.6%
16219269062
 
3.6%
16569526151
 
1.8%
16344496981
 
1.8%
16182435821
 
1.8%
16612645191
 
1.8%
16450396161
 
1.8%
16541015701
 
1.8%
Other values (35)35
62.5%
ValueCountFrequency (%)
16034670371
1.8%
16074646181
1.8%
16085040201
1.8%
16096167881
1.8%
16110394971
1.8%
16114368421
1.8%
16120609221
1.8%
16179867351
1.8%
16182435821
1.8%
16215672851
1.8%
ValueCountFrequency (%)
16622069171
1.8%
16619691591
1.8%
16619598561
1.8%
16614447791
1.8%
16612645191
1.8%
16612547171
1.8%
16611783501
1.8%
16611076721
1.8%
16611067121
1.8%
16610060421
1.8%

_embedded.show._links.self.href
Categorical

HIGH CORRELATION

Distinct45
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size576.0 B
https://api.tvmaze.com/shows/31770
https://api.tvmaze.com/shows/52303
 
3
https://api.tvmaze.com/shows/34940
 
2
https://api.tvmaze.com/shows/52571
 
2
https://api.tvmaze.com/shows/48597
 
1
Other values (40)
40 

Length

Max length34
Median length34
Mean length33.96428571
Min length33

Characters and Unicode

Total characters1902
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)73.2%

Sample

1st rowhttps://api.tvmaze.com/shows/48597
2nd rowhttps://api.tvmaze.com/shows/51471
3rd rowhttps://api.tvmaze.com/shows/52178
4th rowhttps://api.tvmaze.com/shows/54033
5th rowhttps://api.tvmaze.com/shows/49740

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/317708
 
14.3%
https://api.tvmaze.com/shows/523033
 
5.4%
https://api.tvmaze.com/shows/349402
 
3.6%
https://api.tvmaze.com/shows/525712
 
3.6%
https://api.tvmaze.com/shows/485971
 
1.8%
https://api.tvmaze.com/shows/583561
 
1.8%
https://api.tvmaze.com/shows/527371
 
1.8%
https://api.tvmaze.com/shows/528581
 
1.8%
https://api.tvmaze.com/shows/533381
 
1.8%
https://api.tvmaze.com/shows/538901
 
1.8%
Other values (35)35
62.5%

Length

2022-09-05T21:38:35.413513image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/317708
 
14.3%
https://api.tvmaze.com/shows/523033
 
5.4%
https://api.tvmaze.com/shows/349402
 
3.6%
https://api.tvmaze.com/shows/525712
 
3.6%
https://api.tvmaze.com/shows/518121
 
1.8%
https://api.tvmaze.com/shows/521781
 
1.8%
https://api.tvmaze.com/shows/540331
 
1.8%
https://api.tvmaze.com/shows/497401
 
1.8%
https://api.tvmaze.com/shows/503981
 
1.8%
https://api.tvmaze.com/shows/446591
 
1.8%
Other values (35)35
62.5%

Most occurring characters

ValueCountFrequency (%)
/224
 
11.8%
s168
 
8.8%
t168
 
8.8%
h112
 
5.9%
p112
 
5.9%
a112
 
5.9%
o112
 
5.9%
.112
 
5.9%
m112
 
5.9%
e56
 
2.9%
Other values (16)614
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1232
64.8%
Other Punctuation392
 
20.6%
Decimal Number278
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s168
13.6%
t168
13.6%
h112
9.1%
p112
9.1%
a112
9.1%
o112
9.1%
m112
9.1%
e56
 
4.5%
w56
 
4.5%
c56
 
4.5%
Other values (3)168
13.6%
Decimal Number
ValueCountFrequency (%)
541
14.7%
340
14.4%
734
12.2%
430
10.8%
127
9.7%
927
9.7%
224
8.6%
022
7.9%
820
7.2%
613
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/224
57.1%
.112
28.6%
:56
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1232
64.8%
Common670
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/224
33.4%
.112
16.7%
:56
 
8.4%
541
 
6.1%
340
 
6.0%
734
 
5.1%
430
 
4.5%
127
 
4.0%
927
 
4.0%
224
 
3.6%
Other values (3)55
 
8.2%
Latin
ValueCountFrequency (%)
s168
13.6%
t168
13.6%
h112
9.1%
p112
9.1%
a112
9.1%
o112
9.1%
m112
9.1%
e56
 
4.5%
w56
 
4.5%
c56
 
4.5%
Other values (3)168
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1902
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/224
 
11.8%
s168
 
8.8%
t168
 
8.8%
h112
 
5.9%
p112
 
5.9%
a112
 
5.9%
o112
 
5.9%
.112
 
5.9%
m112
 
5.9%
e56
 
2.9%
Other values (16)614
32.3%
Distinct45
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size576.0 B
https://api.tvmaze.com/episodes/1981700
https://api.tvmaze.com/episodes/2332174
 
3
https://api.tvmaze.com/episodes/2358798
 
2
https://api.tvmaze.com/episodes/1990231
 
2
https://api.tvmaze.com/episodes/2269802
 
1
Other values (40)
40 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2184
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)73.2%

Sample

1st rowhttps://api.tvmaze.com/episodes/2269802
2nd rowhttps://api.tvmaze.com/episodes/1956341
3rd rowhttps://api.tvmaze.com/episodes/2259040
4th rowhttps://api.tvmaze.com/episodes/2309442
5th rowhttps://api.tvmaze.com/episodes/2377377

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19817008
 
14.3%
https://api.tvmaze.com/episodes/23321743
 
5.4%
https://api.tvmaze.com/episodes/23587982
 
3.6%
https://api.tvmaze.com/episodes/19902312
 
3.6%
https://api.tvmaze.com/episodes/22698021
 
1.8%
https://api.tvmaze.com/episodes/21956021
 
1.8%
https://api.tvmaze.com/episodes/20564141
 
1.8%
https://api.tvmaze.com/episodes/23780191
 
1.8%
https://api.tvmaze.com/episodes/22774201
 
1.8%
https://api.tvmaze.com/episodes/23378941
 
1.8%
Other values (35)35
62.5%

Length

2022-09-05T21:38:35.502234image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19817008
 
14.3%
https://api.tvmaze.com/episodes/23321743
 
5.4%
https://api.tvmaze.com/episodes/23587982
 
3.6%
https://api.tvmaze.com/episodes/19902312
 
3.6%
https://api.tvmaze.com/episodes/19692471
 
1.8%
https://api.tvmaze.com/episodes/22590401
 
1.8%
https://api.tvmaze.com/episodes/23094421
 
1.8%
https://api.tvmaze.com/episodes/23773771
 
1.8%
https://api.tvmaze.com/episodes/20123271
 
1.8%
https://api.tvmaze.com/episodes/19626741
 
1.8%
Other values (35)35
62.5%

Most occurring characters

ValueCountFrequency (%)
/224
 
10.3%
p168
 
7.7%
s168
 
7.7%
e168
 
7.7%
t168
 
7.7%
o112
 
5.1%
a112
 
5.1%
i112
 
5.1%
.112
 
5.1%
m112
 
5.1%
Other values (16)728
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1400
64.1%
Other Punctuation392
 
17.9%
Decimal Number392
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p168
12.0%
s168
12.0%
e168
12.0%
t168
12.0%
o112
8.0%
a112
8.0%
i112
8.0%
m112
8.0%
h56
 
4.0%
d56
 
4.0%
Other values (3)168
12.0%
Decimal Number
ValueCountFrequency (%)
264
16.3%
157
14.5%
749
12.5%
941
10.5%
039
9.9%
335
8.9%
834
8.7%
425
 
6.4%
625
 
6.4%
523
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/224
57.1%
.112
28.6%
:56
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1400
64.1%
Common784
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/224
28.6%
.112
14.3%
264
 
8.2%
157
 
7.3%
:56
 
7.1%
749
 
6.2%
941
 
5.2%
039
 
5.0%
335
 
4.5%
834
 
4.3%
Other values (3)73
 
9.3%
Latin
ValueCountFrequency (%)
p168
12.0%
s168
12.0%
e168
12.0%
t168
12.0%
o112
8.0%
a112
8.0%
i112
8.0%
m112
8.0%
h56
 
4.0%
d56
 
4.0%
Other values (3)168
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/224
 
10.3%
p168
 
7.7%
s168
 
7.7%
e168
 
7.7%
t168
 
7.7%
o112
 
5.1%
a112
 
5.1%
i112
 
5.1%
.112
 
5.1%
m112
 
5.1%
Other values (16)728
33.3%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing50
Missing (%)89.3%
Memory size576.0 B
https://api.tvmaze.com/episodes/2259041
https://api.tvmaze.com/episodes/2309443
https://api.tvmaze.com/episodes/2377378
https://api.tvmaze.com/episodes/2376729
https://api.tvmaze.com/episodes/2377389

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters234
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2259041
2nd rowhttps://api.tvmaze.com/episodes/2309443
3rd rowhttps://api.tvmaze.com/episodes/2377378
4th rowhttps://api.tvmaze.com/episodes/2376729
5th rowhttps://api.tvmaze.com/episodes/2377389

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/22590411
 
1.8%
https://api.tvmaze.com/episodes/23094431
 
1.8%
https://api.tvmaze.com/episodes/23773781
 
1.8%
https://api.tvmaze.com/episodes/23767291
 
1.8%
https://api.tvmaze.com/episodes/23773891
 
1.8%
https://api.tvmaze.com/episodes/23671071
 
1.8%
(Missing)50
89.3%

Length

2022-09-05T21:38:35.591541image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:35.692895image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/22590411
16.7%
https://api.tvmaze.com/episodes/23094431
16.7%
https://api.tvmaze.com/episodes/23773781
16.7%
https://api.tvmaze.com/episodes/23767291
16.7%
https://api.tvmaze.com/episodes/23773891
16.7%
https://api.tvmaze.com/episodes/23671071
16.7%

Most occurring characters

ValueCountFrequency (%)
/24
 
10.3%
p18
 
7.7%
s18
 
7.7%
e18
 
7.7%
t18
 
7.7%
a12
 
5.1%
i12
 
5.1%
.12
 
5.1%
m12
 
5.1%
o12
 
5.1%
Other values (16)78
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter150
64.1%
Other Punctuation42
 
17.9%
Decimal Number42
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p18
12.0%
s18
12.0%
e18
12.0%
t18
12.0%
a12
8.0%
i12
8.0%
m12
8.0%
o12
8.0%
h6
 
4.0%
d6
 
4.0%
Other values (3)18
12.0%
Decimal Number
ValueCountFrequency (%)
79
21.4%
38
19.0%
28
19.0%
94
9.5%
03
 
7.1%
43
 
7.1%
12
 
4.8%
82
 
4.8%
62
 
4.8%
51
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/24
57.1%
.12
28.6%
:6
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin150
64.1%
Common84
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/24
28.6%
.12
14.3%
79
 
10.7%
38
 
9.5%
28
 
9.5%
:6
 
7.1%
94
 
4.8%
03
 
3.6%
43
 
3.6%
12
 
2.4%
Other values (3)5
 
6.0%
Latin
ValueCountFrequency (%)
p18
12.0%
s18
12.0%
e18
12.0%
t18
12.0%
a12
8.0%
i12
8.0%
m12
8.0%
o12
8.0%
h6
 
4.0%
d6
 
4.0%
Other values (3)18
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/24
 
10.3%
p18
 
7.7%
s18
 
7.7%
e18
 
7.7%
t18
 
7.7%
a12
 
5.1%
i12
 
5.1%
.12
 
5.1%
m12
 
5.1%
o12
 
5.1%
Other values (16)78
33.3%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)100.0%
Missing50
Missing (%)89.3%
Infinite0
Infinite (%)0.0%
Mean325.8333333
Minimum8
Maximum1320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:35.766334image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile13.5
Q145.25
median111.5
Q3313.5
95-th percentile1083.5
Maximum1320
Range1312
Interquartile range (IQR)268.25

Descriptive statistics

Standard deviation504.3690778
Coefficient of variation (CV)1.547935789
Kurtosis4.558196426
Mean325.8333333
Median Absolute Deviation (MAD)92.5
Skewness2.11483485
Sum1955
Variance254388.1667
MonotonicityNot monotonic
2022-09-05T21:38:35.850315image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
81
 
1.8%
13201
 
1.8%
3741
 
1.8%
1321
 
1.8%
911
 
1.8%
301
 
1.8%
(Missing)50
89.3%
ValueCountFrequency (%)
81
1.8%
301
1.8%
911
1.8%
1321
1.8%
3741
1.8%
13201
1.8%
ValueCountFrequency (%)
13201
1.8%
3741
1.8%
1321
1.8%
911
1.8%
301
1.8%
81
1.8%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing50
Missing (%)89.3%
Memory size576.0 B
HBO
UA:Перший
TV Globo
Tokyo MX
NRK1

Length

Max length11
Median length8.5
Mean length7.166666667
Min length3

Characters and Unicode

Total characters43
Distinct characters32
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowHBO
2nd rowUA:Перший
3rd rowTV Globo
4th rowTokyo MX
5th rowNRK1

Common Values

ValueCountFrequency (%)
HBO1
 
1.8%
UA:Перший1
 
1.8%
TV Globo1
 
1.8%
Tokyo MX1
 
1.8%
NRK11
 
1.8%
USA Network1
 
1.8%
(Missing)50
89.3%

Length

2022-09-05T21:38:35.947519image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:36.051036image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
hbo1
11.1%
ua:перший1
11.1%
tv1
11.1%
globo1
11.1%
tokyo1
11.1%
mx1
11.1%
nrk11
11.1%
usa1
11.1%
network1
11.1%

Most occurring characters

ValueCountFrequency (%)
o5
 
11.6%
3
 
7.0%
N2
 
4.7%
U2
 
4.7%
A2
 
4.7%
T2
 
4.7%
k2
 
4.7%
y1
 
2.3%
M1
 
2.3%
X1
 
2.3%
Other values (22)22
51.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter19
44.2%
Uppercase Letter19
44.2%
Space Separator3
 
7.0%
Decimal Number1
 
2.3%
Other Punctuation1
 
2.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N2
 
10.5%
U2
 
10.5%
A2
 
10.5%
T2
 
10.5%
M1
 
5.3%
X1
 
5.3%
H1
 
5.3%
R1
 
5.3%
S1
 
5.3%
K1
 
5.3%
Other values (5)5
26.3%
Lowercase Letter
ValueCountFrequency (%)
o5
26.3%
k2
 
10.5%
y1
 
5.3%
e1
 
5.3%
t1
 
5.3%
w1
 
5.3%
l1
 
5.3%
b1
 
5.3%
й1
 
5.3%
и1
 
5.3%
Other values (4)4
21.1%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
:1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin32
74.4%
Cyrillic6
 
14.0%
Common5
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o5
 
15.6%
N2
 
6.2%
U2
 
6.2%
A2
 
6.2%
T2
 
6.2%
k2
 
6.2%
y1
 
3.1%
M1
 
3.1%
X1
 
3.1%
H1
 
3.1%
Other values (13)13
40.6%
Cyrillic
ValueCountFrequency (%)
й1
16.7%
и1
16.7%
ш1
16.7%
р1
16.7%
е1
16.7%
П1
16.7%
Common
ValueCountFrequency (%)
3
60.0%
11
 
20.0%
:1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII37
86.0%
Cyrillic6
 
14.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o5
 
13.5%
3
 
8.1%
N2
 
5.4%
U2
 
5.4%
A2
 
5.4%
T2
 
5.4%
k2
 
5.4%
y1
 
2.7%
M1
 
2.7%
X1
 
2.7%
Other values (16)16
43.2%
Cyrillic
ValueCountFrequency (%)
й1
16.7%
и1
16.7%
ш1
16.7%
р1
16.7%
е1
16.7%
П1
16.7%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)83.3%
Missing50
Missing (%)89.3%
Memory size576.0 B
United States
Ukraine
Brazil
Japan
Norway

Length

Max length13
Median length7
Mean length8.333333333
Min length5

Characters and Unicode

Total characters50
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st rowUnited States
2nd rowUkraine
3rd rowBrazil
4th rowJapan
5th rowNorway

Common Values

ValueCountFrequency (%)
United States2
 
3.6%
Ukraine1
 
1.8%
Brazil1
 
1.8%
Japan1
 
1.8%
Norway1
 
1.8%
(Missing)50
89.3%

Length

2022-09-05T21:38:36.152249image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:36.257619image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
united2
25.0%
states2
25.0%
ukraine1
12.5%
brazil1
12.5%
japan1
12.5%
norway1
12.5%

Most occurring characters

ValueCountFrequency (%)
a7
14.0%
t6
12.0%
e5
10.0%
i4
 
8.0%
n4
 
8.0%
U3
 
6.0%
r3
 
6.0%
d2
 
4.0%
2
 
4.0%
S2
 
4.0%
Other values (11)12
24.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter40
80.0%
Uppercase Letter8
 
16.0%
Space Separator2
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a7
17.5%
t6
15.0%
e5
12.5%
i4
10.0%
n4
10.0%
r3
7.5%
d2
 
5.0%
s2
 
5.0%
p1
 
2.5%
w1
 
2.5%
Other values (5)5
12.5%
Uppercase Letter
ValueCountFrequency (%)
U3
37.5%
S2
25.0%
N1
 
12.5%
J1
 
12.5%
B1
 
12.5%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin48
96.0%
Common2
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a7
14.6%
t6
12.5%
e5
10.4%
i4
 
8.3%
n4
 
8.3%
U3
 
6.2%
r3
 
6.2%
d2
 
4.2%
S2
 
4.2%
s2
 
4.2%
Other values (10)10
20.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII50
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a7
14.0%
t6
12.0%
e5
10.0%
i4
 
8.0%
n4
 
8.0%
U3
 
6.0%
r3
 
6.0%
d2
 
4.0%
2
 
4.0%
S2
 
4.0%
Other values (11)12
24.0%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)83.3%
Missing50
Missing (%)89.3%
Memory size576.0 B
US
UA
BR
JP
NO

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters12
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st rowUS
2nd rowUA
3rd rowBR
4th rowJP
5th rowNO

Common Values

ValueCountFrequency (%)
US2
 
3.6%
UA1
 
1.8%
BR1
 
1.8%
JP1
 
1.8%
NO1
 
1.8%
(Missing)50
89.3%

Length

2022-09-05T21:38:36.345612image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:36.442792image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
us2
33.3%
ua1
16.7%
br1
16.7%
jp1
16.7%
no1
16.7%

Most occurring characters

ValueCountFrequency (%)
U3
25.0%
S2
16.7%
A1
 
8.3%
B1
 
8.3%
R1
 
8.3%
J1
 
8.3%
P1
 
8.3%
N1
 
8.3%
O1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter12
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U3
25.0%
S2
16.7%
A1
 
8.3%
B1
 
8.3%
R1
 
8.3%
J1
 
8.3%
P1
 
8.3%
N1
 
8.3%
O1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Latin12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U3
25.0%
S2
16.7%
A1
 
8.3%
B1
 
8.3%
R1
 
8.3%
J1
 
8.3%
P1
 
8.3%
N1
 
8.3%
O1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U3
25.0%
S2
16.7%
A1
 
8.3%
B1
 
8.3%
R1
 
8.3%
J1
 
8.3%
P1
 
8.3%
N1
 
8.3%
O1
 
8.3%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)83.3%
Missing50
Missing (%)89.3%
Memory size576.0 B
America/New_York
Europe/Zaporozhye
America/Noronha
Asia/Tokyo
Europe/Oslo

Length

Max length17
Median length15.5
Mean length14.16666667
Min length10

Characters and Unicode

Total characters85
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st rowAmerica/New_York
2nd rowEurope/Zaporozhye
3rd rowAmerica/Noronha
4th rowAsia/Tokyo
5th rowEurope/Oslo

Common Values

ValueCountFrequency (%)
America/New_York2
 
3.6%
Europe/Zaporozhye1
 
1.8%
America/Noronha1
 
1.8%
Asia/Tokyo1
 
1.8%
Europe/Oslo1
 
1.8%
(Missing)50
89.3%

Length

2022-09-05T21:38:36.537869image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:36.634571image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
america/new_york2
33.3%
europe/zaporozhye1
16.7%
america/noronha1
16.7%
asia/tokyo1
16.7%
europe/oslo1
16.7%

Most occurring characters

ValueCountFrequency (%)
o11
 
12.9%
r9
 
10.6%
e8
 
9.4%
a6
 
7.1%
/6
 
7.1%
A4
 
4.7%
i4
 
4.7%
p3
 
3.5%
m3
 
3.5%
k3
 
3.5%
Other values (16)28
32.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter63
74.1%
Uppercase Letter14
 
16.5%
Other Punctuation6
 
7.1%
Connector Punctuation2
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o11
17.5%
r9
14.3%
e8
12.7%
a6
9.5%
i4
 
6.3%
p3
 
4.8%
m3
 
4.8%
k3
 
4.8%
c3
 
4.8%
w2
 
3.2%
Other values (7)11
17.5%
Uppercase Letter
ValueCountFrequency (%)
A4
28.6%
N3
21.4%
Y2
14.3%
E2
14.3%
Z1
 
7.1%
T1
 
7.1%
O1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin77
90.6%
Common8
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o11
14.3%
r9
 
11.7%
e8
 
10.4%
a6
 
7.8%
A4
 
5.2%
i4
 
5.2%
p3
 
3.9%
m3
 
3.9%
k3
 
3.9%
N3
 
3.9%
Other values (14)23
29.9%
Common
ValueCountFrequency (%)
/6
75.0%
_2
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII85
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o11
 
12.9%
r9
 
10.6%
e8
 
9.4%
a6
 
7.1%
/6
 
7.1%
A4
 
4.7%
i4
 
4.7%
p3
 
3.5%
m3
 
3.5%
k3
 
3.5%
Other values (16)28
32.9%

_embedded.show.network.officialSite
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing55
Missing (%)98.2%
Memory size576.0 B
https://www.hbo.com/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters20
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowhttps://www.hbo.com/

Common Values

ValueCountFrequency (%)
https://www.hbo.com/1
 
1.8%
(Missing)55
98.2%

Length

2022-09-05T21:38:36.715319image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:36.793363image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.hbo.com1
100.0%

Most occurring characters

ValueCountFrequency (%)
/3
15.0%
w3
15.0%
h2
10.0%
t2
10.0%
.2
10.0%
o2
10.0%
p1
 
5.0%
s1
 
5.0%
:1
 
5.0%
b1
 
5.0%
Other values (2)2
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14
70.0%
Other Punctuation6
30.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w3
21.4%
h2
14.3%
t2
14.3%
o2
14.3%
p1
 
7.1%
s1
 
7.1%
b1
 
7.1%
c1
 
7.1%
m1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/3
50.0%
.2
33.3%
:1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin14
70.0%
Common6
30.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w3
21.4%
h2
14.3%
t2
14.3%
o2
14.3%
p1
 
7.1%
s1
 
7.1%
b1
 
7.1%
c1
 
7.1%
m1
 
7.1%
Common
ValueCountFrequency (%)
/3
50.0%
.2
33.3%
:1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/3
15.0%
w3
15.0%
h2
10.0%
t2
10.0%
.2
10.0%
o2
10.0%
p1
 
5.0%
s1
 
5.0%
:1
 
5.0%
b1
 
5.0%
Other values (2)2
10.0%

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing55
Missing (%)98.2%
Memory size576.0 B
Ukraine

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUkraine

Common Values

ValueCountFrequency (%)
Ukraine1
 
1.8%
(Missing)55
98.2%

Length

2022-09-05T21:38:36.864793image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:36.947222image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ukraine1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6
85.7%
Uppercase Letter1
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k1
16.7%
r1
16.7%
a1
16.7%
i1
16.7%
n1
16.7%
e1
16.7%
Uppercase Letter
ValueCountFrequency (%)
U1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing55
Missing (%)98.2%
Memory size576.0 B
UA

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUA

Common Values

ValueCountFrequency (%)
UA1
 
1.8%
(Missing)55
98.2%

Length

2022-09-05T21:38:37.026906image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:37.119243image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ua1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing55
Missing (%)98.2%
Memory size576.0 B
Europe/Zaporozhye

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Europe/Zaporozhye1
 
1.8%
(Missing)55
98.2%

Length

2022-09-05T21:38:37.195555image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:37.274763image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/zaporozhye1
100.0%

Most occurring characters

ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14
82.4%
Uppercase Letter2
 
11.8%
Other Punctuation1
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
21.4%
r2
14.3%
p2
14.3%
e2
14.3%
u1
 
7.1%
a1
 
7.1%
z1
 
7.1%
h1
 
7.1%
y1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E1
50.0%
Z1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16
94.1%
Common1
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3
18.8%
r2
12.5%
p2
12.5%
e2
12.5%
E1
 
6.2%
u1
 
6.2%
Z1
 
6.2%
a1
 
6.2%
z1
 
6.2%
h1
 
6.2%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Interactions

2022-09-05T21:38:25.915553image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:16.456238image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:17.514319image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:18.360131image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:19.196183image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:20.060380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:20.874490image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:21.728885image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:22.599784image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:23.398498image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:24.214891image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:25.034876image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:25.990824image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:16.654561image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:17.583671image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:18.437272image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:19.273336image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:20.135815image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:20.945911image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:21.799478image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:22.669749image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:23.468927image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:24.288358image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:25.106901image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:26.056842image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:16.743003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:17.662351image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:18.508815image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:19.349209image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:20.209613image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:21.023176image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:21.881894image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:22.746697image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:23.540318image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:24.366974image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:25.177825image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:26.121002image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:16.827588image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:17.731857image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:18.576526image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:19.415368image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:20.277575image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:21.092643image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:21.953174image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:22.813616image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:23.604713image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:24.436346image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:25.243109image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:26.197731image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:16.908439image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:17.803788image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:18.647588image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:19.490637image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:20.349054image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:21.169302image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:22.028938image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:22.878791image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:23.680243image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:24.508294image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:38:25.386246image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:26.323133image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:17.070825image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:17.947532image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:38:25.460323image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:38:17.152530image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:18.017129image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:38:25.837054image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:38:37.363811image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:38:37.607373image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:38:37.864104image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:38:38.154655image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:38:27.042307image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:38:27.827419image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:38:28.392548image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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02269800https://www.tvmaze.com/episodes/2269800/manaki-1x07-golos-zvera-delo-arhangelskogo-manakaГолос зверя. Дело архангельского маньяка17.0regular2020-12-062020-12-06T00:00:00+00:0040.0NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/394/985941.jpghttps://static.tvmaze.com/uploads/images/original_untouched/394/985941.jpghttps://api.tvmaze.com/episodes/226980048597https://www.tvmaze.com/shows/48597/manakiМаньякиDocumentaryRussian[]To Be Determined40.040.02020-05-22Nonehttps://premier.one/show/12420[]NaN16NaN281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/394/985939.jpghttps://static.tvmaze.com/uploads/images/original_untouched/394/985939.jpg<p>The non-fiction series "Maniacs" tells about the most high-profile Russian crimes, in which still not all the circumstances are clear to the end</p>1656952615https://api.tvmaze.com/shows/48597https://api.tvmaze.com/episodes/2269802NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11956338https://www.tvmaze.com/episodes/1956338/hero-return-1x09-episode-9Episode 919.0regular2020-12-0610:002020-12-06T02:00:00+00:0015.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/195633851471https://www.tvmaze.com/shows/51471/hero-returnHero ReturnAnimationChinese[Action, Anime, Science-Fiction]Running15.016.02020-10-18Nonehttps://v.qq.com/detail/q/q72jd29a3oxflsr.html10:00[Sunday]NaN82NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/279/698895.jpghttps://static.tvmaze.com/uploads/images/original_untouched/279/698895.jpg<p>Zero was mankind's first real superhero. Under his watch, countless other superheros appeared and followed in his footsteps. However, after 5 years of war, Zero disappeared without a trace.<br /><br />(Source: zeroscans)</p>1603467037https://api.tvmaze.com/shows/51471https://api.tvmaze.com/episodes/1956341NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21978217https://www.tvmaze.com/episodes/1978217/swallowed-star-1x03-episode-3Episode 313.0regular2020-12-0610:002020-12-06T02:00:00+00:00NaNNoneNaNNaNNaNhttps://api.tvmaze.com/episodes/197821752178https://www.tvmaze.com/shows/52178/swallowed-starSwallowed StarAnimationChinese[Anime, Science-Fiction]RunningNaN21.02020-11-29Nonehttps://v.qq.com/detail/3/324olz7ilvo2j5f.html10:00[Wednesday]7.793NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN392598.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/286/715165.jpghttps://static.tvmaze.com/uploads/images/original_untouched/286/715165.jpg<p>One day, an unexplained RR virus appeared on the earth, drawing the world into disaster. Infected animals mutated into terrible monsters, invaded massively, and humans built walls around the destruction and established the base city as the last bastion for humans. The suffering that mankind has experienced during this period of time is known as the "Great Nirvana Period." Not only that, Luo Feng not only carried the burden of supporting the family but also to protect the human homeland, for the better survival and development of mankind, together with other justice warriors, to join hands against the fierce monsters. Under the desperate situation of the end, can Luo Feng and other warriors repel monsters and successfully protect the human world?</p>1661959856https://api.tvmaze.com/shows/52178https://api.tvmaze.com/episodes/2259040NaNhttps://api.tvmaze.com/episodes/2259041NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
32052506https://www.tvmaze.com/episodes/2052506/wu-shen-zhu-zai-1x81-episode-81Episode 81181.0regular2020-12-0610:002020-12-06T02:00:00+00:008.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/205250654033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese[Action, Adventure, Anime, Fantasy]Running8.08.02020-03-08Nonehttps://v.qq.com/detail/m/7q544xyrava3vxf.html10:00[Tuesday, Sunday]NaN82NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN379070.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>1649423444https://api.tvmaze.com/shows/54033https://api.tvmaze.com/episodes/2309442NaNhttps://api.tvmaze.com/episodes/2309443NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42138924https://www.tvmaze.com/episodes/2138924/tokyo-joshi-pro-wrestling-2020-12-06-tjpw-fall-tour-20-womm-wrestling-of-my-mindTJPW Fall Tour '20 ~ WOMM (Wrestling Of My Mind) ~202042.0regular2020-12-0612:002020-12-06T03:00:00+00:00120.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/213892449740https://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestlingTokyo Joshi Pro WrestlingSportsJapanese[]Running120.0120.02013-01-30Nonehttps://www.ddtpro.com/12:00[Saturday]NaN46NaN408.0DDTUniverseJapanJPAsia/TokyoNoneNaNNaN375304.0tt10784214https://static.tvmaze.com/uploads/images/medium_portrait/268/670796.jpghttps://static.tvmaze.com/uploads/images/original_untouched/268/670796.jpgNone1661106712https://api.tvmaze.com/shows/49740https://api.tvmaze.com/episodes/2377377NaNhttps://api.tvmaze.com/episodes/2377378NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52012320https://www.tvmaze.com/episodes/2012320/mans-diary-2x05-episode-5Episode 525.0regular2020-12-062020-12-06T04:00:00+00:0012.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/201232050398https://www.tvmaze.com/shows/50398/mans-diaryMan's DiaryAnimationChinese[Anime, Supernatural]Running12.012.02019-07-21Nonehttps://www.bilibili.com/bangumi/media/md4314622[Sunday]NaN4NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNaNNaN379528.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/273/683332.jpghttps://static.tvmaze.com/uploads/images/original_untouched/273/683332.jpg<p>In the twenty-first century, gods and demons can no longer maintain balance due to the rapid development of human society. In an effort to restore proper order, the gods began to take care of saving the world, for which they sent a group of gods and monsters to the world of people, who must find there the " key " to salvation. Su moting is a girl with the personality of "demon child". When her parents asked her to leave home so that she could become independent and independent, she met the beautiful and charming God of Tianjin and the mysterious demon cat. So begins a new turbulent round of su moting's life.</p><p><br /> </p>1611039497https://api.tvmaze.com/shows/50398https://api.tvmaze.com/episodes/2012327NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
61957067https://www.tvmaze.com/episodes/1957067/atlantic-crossing-1x07-gavenGaven17.0regular2020-12-0606:002020-12-06T05:00:00+00:0054.0<p>Märtha ends up in a quandary when the president announces that he wants to support Norway and asks her to say how she feels about him.</p>8.3https://static.tvmaze.com/uploads/images/medium_landscape/284/711894.jpghttps://static.tvmaze.com/uploads/images/original_untouched/284/711894.jpghttps://api.tvmaze.com/episodes/195706744659https://www.tvmaze.com/shows/44659/atlantic-crossingAtlantic CrossingScriptedNorwegian[Drama, War, History]EndedNaN55.02020-10-252020-12-13https://tv.nrk.no/serie/atlantic-crossing06:00[Sunday]8.072NaN238.0NRK TVNorwayNOEurope/OsloNoneNaNNaN366083.0tt9348700https://static.tvmaze.com/uploads/images/medium_portrait/217/542797.jpghttps://static.tvmaze.com/uploads/images/original_untouched/217/542797.jpg<p>1940. Norway is occupied by Nazi Germany. Crown Princess Märtha and her children find shelter as political refugees in the White House. Her presence in Washington soon influences President Roosevelt's views on the tragic events unfolding in Europe and eventually changes the dynamics of U.S. politics significantly. What starts as an affair turns into love and turmoil when Märtha speaks out publicly against the Nazi tyranny. In an attempt to fight for her country, she puts her marriage at risk and convinces the President to support Norway – a first step in the struggle that will lead to the U.S. joining the War. However, Märtha's actions cause her to make many enemies, some of them even closer than she thinks: within the walls of the White House.</p>1648485508https://api.tvmaze.com/shows/44659https://api.tvmaze.com/episodes/1962674NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71977314https://www.tvmaze.com/episodes/1977314/stjernestov-1x06-episode-6Episode 616.0regular2020-12-0606:002020-12-06T05:00:00+00:0018.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726340.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726340.jpghttps://api.tvmaze.com/episodes/197731450752https://www.tvmaze.com/shows/50752/stjernestovStjernestøvScriptedNorwegian[Drama, Children, Family]Ended20.020.02020-12-012020-12-24https://tv.nrk.no/serie/stjernestoev06:00[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN20NaN238.0NRK TVNorwayNOEurope/OsloNoneNaNNaN392649.0tt11492320https://static.tvmaze.com/uploads/images/medium_portrait/288/721951.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/721951.jpg<p>The parents get divorced and Jo has to move to a new place. One day, Nordstjerna goes out, and Jo discovers that a girl with magical powers lives in the attic.</p>1611436842https://api.tvmaze.com/shows/50752https://api.tvmaze.com/episodes/1977332NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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91965922https://www.tvmaze.com/episodes/1965922/new-japan-pro-wrestling-2020-12-06-world-tag-league-2020best-of-the-super-jr27-night-9WORLD TAG LEAGUE 2020/BEST OF THE SUPER Jr.27 Night 9202085.0regular2020-12-0618:002020-12-06T09:00:00+00:00120.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/196592224963https://www.tvmaze.com/shows/24963/new-japan-pro-wrestlingNew Japan Pro WrestlingSportsJapanese[]Running120.098.02015-01-04Nonehttp://www.njpw1972.com/[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN80NaN160.0NJPW WorldJapanJPAsia/TokyoNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/96/240462.jpghttps://static.tvmaze.com/uploads/images/original_untouched/96/240462.jpg<p><b>New Japan Pro Wrestling</b> (NJPW) is the largest professional wrestling promotion in Japan and the second largest promotion in the world.</p>1661006042https://api.tvmaze.com/shows/24963https://api.tvmaze.com/episodes/2376728NaNhttps://api.tvmaze.com/episodes/2376729NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

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idurlnameseasonnumbertypeairdateairtimeairstampruntimesummaryrating.averageimage.mediumimage.original_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage_embedded.show._links.nextepisode.href_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel_embedded.show.image_embedded.show.webChannel.country_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
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472004130https://www.tvmaze.com/episodes/2004130/wwe-24-2020-12-06-keith-leeKeith Lee20207.0regular2020-12-062020-12-06T17:00:00+00:0060.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/20041307591https://www.tvmaze.com/shows/7591/wwe-24WWE 24DocumentaryEnglish[Sports]Running60.057.02015-01-26Nonehttp://network.wwe.com/shows/original/wwe-24[Tuesday]NaN53NaN15.0WWE NetworkUnited StatesUSAmerica/New_YorkNoneNaNNaN291489.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/401/1002761.jpghttps://static.tvmaze.com/uploads/images/original_untouched/401/1002761.jpg<p><b>WWE 24</b> takes you behind the scenes of some of the biggest WWE Pay Per Views in WWE history.</p>1648093787https://api.tvmaze.com/shows/7591https://api.tvmaze.com/episodes/2154708NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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521977560https://www.tvmaze.com/episodes/1977560/peytons-places-2x02-john-elwayJohn Elway22.0regular2020-12-062020-12-06T17:00:00+00:0030.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/197756043207https://www.tvmaze.com/shows/43207/peytons-placesPeyton's PlacesDocumentaryEnglish[History, Sports]Running30.029.02019-07-29Nonehttp://www.espn.com/watch/series/2043dd20-9cc0-4abe-b652-c8e7dfdfefa0/peyton-s-places[Sunday]NaN41NaN265.0ESPN+United StatesUSAmerica/New_YorkNoneNaNNaN362863.0tt10241812https://static.tvmaze.com/uploads/images/medium_portrait/206/516930.jpghttps://static.tvmaze.com/uploads/images/original_untouched/206/516930.jpg<p><b>Peyton's Places</b> offers a fun, insightful tour through 100 years of football, following the sport and the league's rise to an American cultural touchstone. For nearly a year, Manning has crisscrossed the country, visiting the people and places that have played an important part in the making of the NFL—highlighting memorable events, teams, players, and trends over the past century.</p>1647692257https://api.tvmaze.com/shows/43207https://api.tvmaze.com/episodes/2043448NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
531969227https://www.tvmaze.com/episodes/1969227/til-deg-fra-meg-1x02-episode-2Episode 212.0regular2020-12-0622:202020-12-06T21:20:00+00:0029.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/285/714231.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/714231.jpghttps://api.tvmaze.com/episodes/196922751894https://www.tvmaze.com/shows/51894/til-deg-fra-megTil deg fra megRealityNorwegian[]To Be Determined30.029.02020-11-29Nonehttps://tv.nrk.no/serie/til-deg-fra-meg22:15[Sunday]NaN3NaN238.0NRK TVNorwayNOEurope/OsloNoneNaNNaNNaNNoneNaNNaN<p>In this year's Advent series, Per Sundnes meets people who are going to give away a Christmas song. They themselves have experienced more adversity than most of us. Who do they want to give a special Christmas song to?</p>1608504020https://api.tvmaze.com/shows/51894https://api.tvmaze.com/episodes/1969229NaNNaN91.0NRK1NorwayNOEurope/OsloNoneNaNNaNNaNNaNNaNNaN
541972308https://www.tvmaze.com/episodes/1972308/wwe-nxt-s14-special-nxt-takeover-wargamesNXT TakeOver: WarGames14NaNsignificant_special2020-12-0619:002020-12-07T00:00:00+00:00180.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/19723082266https://www.tvmaze.com/shows/2266/wwe-nxtWWE NXTSportsEnglish[]Running120.077.02010-02-23Nonehttp://www.wwe.com/inside/networkschedule20:00[Tuesday]7.292NaN15.0WWE NetworkUnited StatesUSAmerica/New_YorkNoneNaN25100.0144541.0tt1601141https://static.tvmaze.com/uploads/images/medium_portrait/401/1002762.jpghttps://static.tvmaze.com/uploads/images/original_untouched/401/1002762.jpg<p>Each Wednesday at 8:00 p.m. ET, WWE Superstars and Divas of tomorrow face off on <b>WWE NXT</b><i>,</i> a one-hour weekly show that features the brightest and best of WWE's rising stars. WWE NXT showcases the Superstars and Divas from WWE's Performance Center as well as appearances from WWE Superstars and Legends in an intimate setting. WWE NXT broadcasts from the state-of-the-art Full Sail LIVE venue on the Full Sail University in campus in Orlando, Florida.</p>1661969159https://api.tvmaze.com/shows/2266https://api.tvmaze.com/episodes/2383154NaNhttps://api.tvmaze.com/episodes/236710730.0USA NetworkUnited StatesUSAmerica/New_YorkNoneNaNNaNNaNNaNNaNNaN
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